judy heenan, final draft summer 2016 - auburn university
TRANSCRIPT
Learning Styles of Older Adults in Educational Settings
by
Judith Ann Heenan
A dissertation submitted to the Graduate Faculty of Auburn University
in partial fulfillment of the requirements for the Degree of
Doctor of Philosophy
Auburn, Alabama August 6, 2016
Keywords: learning preferences, older learners, baby boomers, retirees, education, andragogy
Approved by
James Witte, Chair, Professor of Educational Foundations, Leadership and Technology Maria Witte, Professor of Educational Foundations, Leadership and Technology Leslie Cordie, Professor of Educational Foundations, Leadership and Technology
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Abstract
Learning Styles of Older Adults in Educational Settings, is an investigation into the
learning styles of the baby boomer generation who are now entering retirement. With typical
retirement at 65 years of age and life expectancy now 80 to 85 years of age, millions of retirees
will have fifteen to twenty years of healthy retirement to fill. This change has created a new
demographic of older adults--baby boomers. Today’s seniors want to be productive during
retirement and many plan to use those years to fulfill dreams and goals postponed during child
rearing years, or when careers took priority. The activities seniors want to pursue will require
further education, training, or new learning and millions of older adults who will be entering
learning environments to acquire the skills necessary to remain active and engaged during the
retirement years (Narushima, Liu, & Diestelkamp, 2013; Parks, Evans, & Getcg, 2013). Studies
reveal that remaining involved in life and pursuing new learning experiences promotes not only a
longer life but, a healthier, more fulfilling, and meaningful life in the senior years, reducing the
dependency on social services and thus taxpayers (Taylor, Morin, Parker, Cohn, & Wang, 2009).
Universities, community colleges, technical, and trade schools, as well as civic
organizations, government agencies, and non-profit organizations must be prepared to meet the
learning needs of this new demographic of older adults who will be entering retirement and
seeking educational opportunities that will allow them to fully participate in a healthy lifestyle,
both mentally and physically. This study was conducted to determine the learning style
preferences of older adults, and will prepare educators and instructors to adapt to the needs of
this new demographic of learners. Participants were surveyed by age, race, and sex using the four
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constructs of the Gregorc Learning Style Delineator: Concrete Sequential, Abstract Sequential,
Concrete Random and Abstract Random (Gregorc, 1984).
Three chi square analyses were conducted to assess the learning preference of each of the
participants according to each category of age, sex, and race with results indicating categorical
preferences. Learning style preferences showed no statistical significance between different ages
and sexes. However, the difference between the learning style preferences by race was
statistically significant. Individual characteristics vary, but this research provides generalizations
as a guideline to assess learner needs and will be of vital importance to the success of new
learning for our older adult population especially in racially diverse learning environments.
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Acknowledgments
I sincerely appreciate the opportunity to advance my studies with a terminal degree in
Adult Education which I proudly consider the preeminent field in academia. My professors and
committee members: professors James Witte, Maria Witte, and Leslie Cordie were innovative
and inspirational in their teaching methods and will continue to be an influence throughout my
career. Faculty and students at Auburn University have expanded my world view to include
multicultural and diverse aspects of teaching and I aspire to eventually match their expertise. I
would like to thank all of the gracious participants in my research study, and the respective
directors of the agencies who kindly allowed this research to take place at their organizations:
Linda Shook, director of Auburn University OLLI, Jackie Pinkard, director of the Lee-Russell
Area Agency on Aging, and Rev. C. Lynn Hopkins of the Montgomery Unitarian Universalist
Fellowship. I would also like to thank the Auburn University Graduate School for funding my
research and the University reader, Dr. Lee Ann Alderman. A special thanks goes to Ron and
Joan Belcher of Montgomery AL, who were always there to lend much needed support. I will
genuinely miss Auburn University and all of the wonderful people I have met.
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Table of Contents
Abstract ......................................................................................................................................... ii
Acknowledgments ....................................................................................................................... iv
List of Tables ................................................................................................................................ x
List of Figures .............................................................................................................................. xi
Chapter 1: Introduction ................................................................................................................. 1
Background ....................................................................................................................... 1
Statement of Problem ...................................................................................................... 5
Purpose of Study ............................................................................................................. 7
Research Questions .......................................................................................................... 7
Significance of the Study .................................................................................................. 7
Assumptions ................................................................................................................... 10
Limitations ..................................................................................................................... 11
Definition of Terms........................................................................................................ 11
Summary ........................................................................................................................ 12
Chapter 2: Literature Review ...................................................................................................... 14
Purpose of the Study ....................................................................................................... 14
Research Questions ......................................................................................................... 14
Seniors in Later Years ..................................................................................................... 15
Successful Aging .................................................................................................. 16
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Making Decision to Learn .................................................................................... 17
Learning Style Models………………………………………………………………….22
Kolb’s Learning Style Inventory………………………………………………...22
Felder & Silverman’s Learning Style Model……………………………………23
Barriers to Learning ...................................................................................................... 24
Education Equals More Education ...................................................................... 24
Agism .................................................................................................................. 27
Digital Age .......................................................................................................... 27
Transportation ..................................................................................................... 28
Seniors in Rural Areas ........................................................................................ 28
Older Women and Men in Education ................................................................. 29
Older Women and Men in the Workplace .......................................................... 30
Older African American and Caucasians in Education ...................................... 34
Older African American Women in Education .................................................. 34
Prohibitive Costs ................................................................................................. 35
Activities of Successful Aging....................................................................................... 36
Working in Later Years ...................................................................................... 36
Volunteerism – Giving Back .............................................................................. 40
Entrepreneurship ................................................................................................. 41
Formal Education in Later Years ........................................................................ 42
A Successful College Transition ......................................................................... 44
Life-long Learning Institutes .............................................................................. 45
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Cognitive Changes in Older Adults ............................................................................... 49
The Aging Brain ................................................................................................. 49
Improving Cognitive Decline ............................................................................. 50
Neuro-Plasticity .................................................................................................. 51
The Scaffolding Theory ...................................................................................... 53
Lifestyles and Cognitive Decline ........................................................................ 55
Models of Aging ............................................................................................................ 60
Erikson’s Generalization ..................................................................................... 60
Hierarchical Model ............................................................................................. 61
The Gregorc Learning Style Delineator .............................................................. 64
Summary ......................................................................................................................... 65
Chapter 3: Methods ..................................................................................................................... 66
Purpose of Study ............................................................................................................ 66
Research Questions ........................................................................................................ 67
Methods.......................................................................................................................... 67
Sample............................................................................................................................ 68
Participants .......................................................................................................... 68
Data Collection ................................................................................................... 69
Statistical Methods .............................................................................................. 69
Instrumentation ............................................................................................................... 70
The Instrument .................................................................................................... 73
Validity ............................................................................................................... 74
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Reliability ............................................................................................................ 76
Data Collection ............................................................................................................... 77
Data Analysis .................................................................................................................. 78
Summary ......................................................................................................................... 79
Chapter 4: Findings ..................................................................................................................... 80
Purpose of the Study ........................................................................................................ 80
Research Questions .......................................................................................................... 80
Demographic Results ....................................................................................................... 81
Population Characteristics .................................................................................. 81
Statistical Frequencies ........................................................................................ 81
Learning Style Frequencies ................................................................................. 81
Learning Styles by Age ....................................................................................... 82
Learning Styles by Sex ....................................................................................... 83
Learning Styles by Race ..................................................................................... 84
Chi Square Tests .............................................................................................................. 85
Phi Coefficients …………………………………………………………………………86
Results ............................................................................................................................. 86
Summary ......................................................................................................................... 87
Chapter 5: Summary, Conclusions, Implications, and Recommendations for Future Research 88
Research Questions ........................................................................................................... 88
Summary ........................................................................................................................... 88
Conclusions ....................................................................................................................... 90
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Implications……………………………………………………………………………....91
Educator Implications ............................................................................................ 91
Participant Implications………………………………………………………..…93
Recommendations……………………………………………………………………….93
References ................................................................................................................................... 96
Appendix A Collaborative Institutional Training Initiative ..................................................... 113
Appendix B Auburn University Institutional Review Board .................................................... 118
Appendix C Demographic Questionnaire ................................................................................. 121
Appendix D Osher Lifelong Learning Institute Auburn, AL ................................................... 122
Appendix E Unitarian Universalist Fellowship, Montgomery, AL.. ................................ ……123
Appendix F Lee-Russell Council of Governments, Opelika AL………………………………124
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List of Tables
Table 1: Gregorc Learning Style Preferences ............................................................................. 82
Table 2: Gregorc Learning Style Delineator Results by Age ..................................................... 83
Table 3: Gregorc Learning Style Delineator Results by Sex ...................................................... 84
Table 4: Gregorc Learning Style Delineator Results by Race ................................................... 85
Table 5: Chi Square Values of Age, Sex, and Race.................................................................... 86
Table 6: Measures of Association of Chi Squares and Phi Coefficients .................................... 87
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List of Figures
Figure 1.1: Life Expectancy 1900-2006 ...................................................................................... 2
Figure 1.2: The Birth of the Boomer ............................................................................................ 3
Figure 1.3 The Boomer Years ....................................................................................................... 4
Figure 1.4: Older Population Projected to 2050 ......................................................................... 10
Figure 2.1: Percentage of Older Adults Who Rate Themselves in Excellent Health ................. 15
Figure 2.2: Rationale for Working in Retirement ....................................................................... 20
Figure 2.3: Older Adults Holding Bachelor’s Degrees or by Race ............................................ 26
Figure 2.4: Older Population with an Associate’s Degree by Race ........................................... 26
Figure 2.5: Older Men and Women in the Workplace 1950 and 2004 ....................................... 31
Figure 2.6: Plans to Work in Retirement .................................................................................... 33
Figure 2.7: Workforce Participation Rates ................................................................................ 33
Figure 2.8: Percentage of Retired by Age .................................................................................. 38
Figure 2.9: Difference Between How Old We Feel and Actual Age .......................................... 39
Figure 2.10: Percentage Feeling Younger, Older, or Same as Actual Age……………………. 40
Figure 2.11: Education Participation Among Older Adults…………………………………….43
Figure 3.1: Chi Square Formula…………………………………………………………………70
Figure 3.2: Characteristics of Learning Styles ………………………………………………….71
Figure 5.1: Teaching Strategies to Match Learning Styles...…………………………………….93
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Chapter 1: Introduction
“Anyone who stops learning is old, whether at twenty or eighty. Anyone who keeps learning
stays young. The greatest thing in life is to keep your mind young” (Henry Ford).
Background
America is aging. In 2009 there were 39.6 million Americans aged 65 and older. By
2030 there will be 72.1 million Americans over the age of 65 causing this age group to increase
dramatically from just 12% of the population to almost 20% (US Department of Health and
Human Services, 2009). This upward trend is the result of the baby boomer generation reaching
and entering the retirement years. In 1950, the average life expectancy of Americans was 68
years (Gendell & Siegel, 1992). People were expected to work most of their lives until health
conditions caused retirement, but today with better health care and healthier lifestyles people are
living into their 90s and enjoying good health throughout their 60s and 70s. Figure 1.1 represents
the gradual increase in life expectancy since 1900. Today, the average age of retirement is 62
years, and life expectancy is 80 to 85 years leaving millions of retirees fifteen to twenty years of
healthy active retirement to fill (Rausch, 2013). This change has created a new demographic of
adults. Older adults now want to enjoy retirement, and many plan to use those years to fulfill
dreams and goals postponed during child rearing years, or when careers took priority. Many will
use this time to finish a college degree, attain a higher degree, learn a new skill at a trade or
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Figure 1.1: Life Expentancy 1900-2006
Adapted from Centers for Disease Control and Prevention, National Center for Health Statistics
vocational school, start a new career, or a new business, take classes at senior centers such as
yoga, or computer skills, learn a new sport like golf or swimming, develop a new talent taking
singing, music or dance lessons, and many will volunteer at non-profits, faith based
organizations, libraries, museums, and hospitals. All of these activities will require further
education, training, or new learning (Fairlie, 2006), and millions of older adults will be entering
these learning environments to acquire the skills necessary to remain active and engaged during
the retirement years. Universities, community colleges, technical and trade schools, as well as
civic organizations, government agencies, and non-profit organizations must be prepared to meet
the learning needs of this new demographic of older adults who will be entering retirement and
seeking educational opportunities that will allow them to maintain a fruitful and productive life
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(Erikson, Erikson, & Kivnick, 1994). Bolded years in Figure 1.2 represent the increase in U.S.
births from 1946 to 1964 (represented in the thousands) after soldiers returned from World War
II and started families. Figure 1.3 illustrates the baby boomer years figuratively from 1946 to
1964.
1940 2,559 1955 4,097 1970 3,731 1985 3,761
1941 2,703 1956 4,218 1971 3,556 1986 3,757
1942 2,989 1957 4,300 1972 3,258 1987 3,809
1943 3,104 1958 4,255 1973 3,137 1988 3,910
1944 2,939 1959 4,245 1974 3,160 1989 4,041
1945 2,858 1960 4,258 1975 3,144 1990 4,158
1946 3,411 1961 4,268 1976 3,168 1991 4,111
1947 3,817 1962 4,167 1977 3,327 1992 4,065
1948 3,637 1963 4,098 1978 3,333 1993 4,000
1949 3,649 1964 4,027 1979 3,494 1994 3,979
1950 3,632 1965 3,760 1980 3,612
1951 3,823 1966 3,606 1981 3,629
1952 3,913 1967 3,521 1982 3,681
1953 3,965 1968 3,502 1983 3,639 1954 4,078 1969 3,606 1984 3,669
Figure 1.2. The Birth of the Boomer
Source: Copyright 1998-2011 Baby Boomer Head Quarters- wwwbbhq.com
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According to Gendell and Siegel (1992), the number of retired Americans over the age of 65
will double by 2020, and these older adults will be entering educational environments in record
numbers. Barriers to learning must be overcome by older adults, and educators in academic
settings must be prepared to meet the learning challenges facing older learners. The educational
environment must be able to adapt to the needs of older learners by using adaptive teaching
strategies as well as physical accommodations. Implications for educators and administrators
include: agism, stereotyping, mobility, transportation problems, and the physical limitations
inherent with aging (Coudin & Alexopoulos, 2010). Moreover, an awareness of the barriers to
learning, an understanding of learning preferences, and learning styles of older adults will be
crucial in providing programs and services that meet the needs of the increasing number of
retirees entering learning environments.
Figure 1.3 The Boomer Year
Source: Copyright 1998-2011. Baby Boomer Head Quarters-wwwbbhq.com
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Today, older adults entering formal and informal learning environments are more diverse
than older adult learners of the past (Cruce & Hillman, 2012), and require policy or procedural
changes, and new strategies to accommodate the learning styles and needs of these learners who
want to remain active and engaged during the retirement years. As educators, it is incumbent
upon us to develop awareness, and create a vision for this new demographic of students as
millions of baby boomers enter retirement and redefine our concept of this stage of life.
Statement of the Problem
Current research lacks an expanded definition of the learning styles of older adults
especially the current population of seniors who will be overwhelming learning institutions. “The
sheer magnitude of people slated to reach late adulthood within the next few decades makes the
quest to understand the precursors of successful aging a public priority” (Pruchno, Genderson,
Rose, & Cartwright, 2010, p. 821). According to Truluck and Courtney (1999), the learning style
preferences of children and adolescents has been extensively researched; however, there is a lack
of research related to the learning styles of older adults. Learning style inventories such as David
Kolb’s experiential model is best suited for class room environments, and Peter Honey and Alan
Mumford’s model is best suited for adults in an employment related environment. Even Neil
Fleming’s VAK/VARK model identifies learning styles as simply visual, auditory, reading, or
kinesthetic.
A more comprehensive understanding of the learning styles and preferences of older
adults is necessary to meet the learning needs of the large influx of baby boomers soon to retire
and seek learning opportunities in a wide variety of educational settings. Fewer studies have
investigated the learning styles and preferences of older adults and with this population of adults
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increasing exponentially, an investigation of this specific cohort of seniors can serve as a
template for learning scenarios and practices for future generations.
In the past, research related to elders usually explored plans for retirement, health care,
and end-of-life issues leaving little information on participation in educational endeavors or an
understanding of the learning preferences and styles of older adults. Furthermore, research of the
past has focused on older adults who are white, middle class, and highly educated leaving racial
minorities, new immigrants, and elders in rural areas, under investigated and underserved (Kim
& Merriam, 2004). Seniors from previous generations may have been tested to determine
learning styles. However, the current cohort of adults over 65 years of age, has not yet been
sufficiently tested as to their learning style in relation to age. If tested previously in their adult
lives, current results would differ due to cognitive changes in the function of the older adult brain
and in the neural pathways used to acquire and retain new knowledge (Manard, Carabin, Jaspar,
& Collette, 2014). An assessment of learning styles of this generation at an advanced age is
imperative not only for these seniors, but for generations of senior learners in the future.
The baby boomers cover two distinct generations, and older learners can be divided into
two separate age groups, young-old adults (65-74) and old-old adults (75-99) (Ginsberg & Lynn,
2002). This study will identify the learning styles of each age group using the Gregorc Learning
Style Delineator. Also, using the Gregorc Delineator differences in learning styles between men
and women, and race: African American and Caucasian, were assessed. These distinctions will
add value and significance to this study by examining specific demographics within this current
population of older adults, thereby contributing to the existing body of scientific inquiry in the
field of Adult Education.
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Purpose of the Study
The purpose of this study was to identify the learning styles of older adults using the
Gregorc Learning Style Delineator. In this study, older adults were ages 65 to 75 years or over
75 years of age. This study also identified race (African American or Caucasian), and sex (male
or female) as additional variables. Data were collected from participants in university life-long
learning programs, an area agency on aging, and faith-based settings. This study sought to
ascertain the learning styles that were used by older learners or groups of older learners.
Learning style instruments, such as the Gregorc Learning Style Delineator, assist individuals in
building an awareness or identifying learning and teaching practices that are best suited to their
own cognitive abilities.
Research Questions
The following research questions were used in this study:
1. What are the learning styles of older adults in relation to age?
2. What are the learning styles of older adults in relation to sex?
3. What are the learning styles of older adults in relation to race?
Significance of this Study
The results of this study will prepare educators, educational institutions, and program
administrators for the influx of older adults who will enter educational settings in the near future.
By 2030 seventy million adults will be 65 years of age and older—20% of the US population
(US Census Bureau, 2004; Lakin, Mullane, & Robinson, 2007). By 2050, Figure 1.4 projects the
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population over 65 years of age to increase to one in five Americans compared to one in eight
today (Taylor, et al., 2009). According to Shinagel (2012), by 2050 the number of Americans
over 65 is now projected by the US Census Bureau to be 88.5 million which is more than double
the 2010 projected number of 40.2 million. Current research and organizational surveys from the
Pew Research Center’s, Growing Old in America (2009), and The Met Life Foundation’s,
Framing New Terrain: Older Adults & Higher Education indicate that most of these senior
citizens plan to maintain active and engaged lifestyles, leaving learning institutions and
organizations to potentially contend with one-fifth of our nation’s population seeking
opportunities to remain connected (Lakin, et al, 2007). Learning environments could become
overwhelmed, and resources in educational settings could be stretched to unprecedented levels,
while educators would be unprepared to meet the demands of these new learners. Higher
education administrators, instructors, policymakers, non-profit administrators, business owners,
and leaders of government and religious organizations must be aware of the implications for their
organization regarding funding, strategic planning, implementation, resource allocation, and
more importantly for instructors who must learn to accommodate the learning styles of this
influx of new older students.
Seniors will be seeking activities that will improve their self-esteem, develop talents and
skills, increase retirement income, achieve career and personal goals, and improve their quality
of life (Cruse & Hillman, 2012). To better meet these needs a statistical analysis will identify the
learning styles of older learners, and allow educators to potentially modify teaching strategies
that would include methods that address each of the four learning styles identified by the
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Gregorc Learning Style Delineator: Concrete Sequential, Abstract Sequential, Abstract Random,
and Concrete Random.
Furthermore, an increase in the awareness of future trends and learning styles in
educational settings will allow a clearer perspective of the expectations of seniors in learning
environments, and enable educators to facilitate learning for elders by being aware of learning
styles in regard to age, sex, and racial differences within this population.
The results of this study will add to the limited existing body of knowledge in regards to
older learners by preparing educators and administrators for the large influx of elders entering
learning environments. Furthermore, educators can apply distinct learning principles to
individual older learners or groups of older learners. The learning styles identified by the
Gregorc Learning Style Delineator will further assist individuals to self-identify the teaching
practices best suited to their own cognitive abilities.
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Figure 1.4 Older Population Projected to 2050
Adapted from 1900 – 2008 Census Bureau. 2010–2050 projections are based on a starting point
of 2005, Pew Research Center.
Assumptions
The following assumptions were made with this study:
1) The Gregorc Style Delineator was a valid instrument to identify the learning styles of older
adults.
2) The participants understood the questionnaire and were able to answer the questions honestly
and consistently.
3) The participants in this study are representative of the older adult population in central
Alabama.
Limitations
The following limitations apply to this study:
1) The limitations of this study relate to the geographic area of central Alabama and may not be
generalizable to older adults in other areas of the United States.
2) This study is limited to the results of the Gregorc Learning Style Delineator which is not
intended as an all-inclusive assessment of learning, but as an evaluation tool for self-analysis
(Gregorc, 1984).
3) The selected sample population of this study was limited to older adults who possessed the
cognitive ability to volunteer to have their learning style measured and the ability to understand
the directions given by the researcher to complete the survey.
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Definition of Terms
Andragogy- specific learning methods that cater to the learning needs of adults: A need to know
why certain information must be learned, autonomy in the classroom, internal motivation
to learn, responsible learners, and life or task oriented learners who have a mutually
cooperative relationship with the instructor (Taylor, & Kroth, 2009).
Agism- the affective, cognitive, behavioral, and institutional prejudice against an older person
that is based on the premise of a uniform relationship between chronological age and
functional limitations (Palmore, Branch, & Harris, 2005).
Baby boomers–the two generations of individuals born between 1946 and 1964.
Crystalized memory-uses skills and knowledge garnered from a lifetime of experiences and
relies somewhat on long term memory.
Episodic memory–long term memory
Executive processing–higher level functioning: reasoning, analysis, and memory.
Fluid intelligence-the ability to solve novel problems with deductive and inductive reasoning
and logic.
Forebrain and prefrontal cortex–also known as grey matter, responsible for executive
processing.
Neuro-chemical transmitters-chemical signals passed from one brain cell (neuron) to the next.
Neuro-plasticity-the ability of neurons to create new neural pathways when previous pathways
are no longer available.
Pedagogy-teacher focused educational practices based on the dependency of the student to the
teacher to provide subject information (Taylor & Kroth, 2009).
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Phenomenology-a research method using techniques to measure the perception or emotional
response of the participants (Gregorc, 1984).
Synaptic sites–on brain cell neurons that either excite or inhibit neuro-chemical transmission.
Summary
The intent of this research study was to further expand the body of scientific knowledge
and provide a more comprehensive definition of how older adults learn new information. This
study will provide recommendations as to how educators can prepare programs that will address
the needs of this generation of older learners entering educational settings. Resource allocation
and curriculum planning are important components when considering the learning styles of older
adults. Educators, administrators, and policy makers must be aware of these components in
order to make informed decisions on curriculum planning, design, implementation, and
evaluation of older adult programs, training, classes, and lessons.
Chapter 1 has explained the necessity of educational programs that address the learning
styles of older adults as retirement age is reached and provided insight to educators, and others
who will administer educational programs, regarding the large numbers of older learners to
expect in the upcoming years. In addition to describing the large number of seniors entering
educational settings, Chapter 1 further explained the significance of examining the current cohort
of seniors in regard to learning styles by age, sex, and race. Chapter 2 provides a literature
review of seniors in retirement, successful aging, learning style models, barriers to learning for
elders, learning institutions specifically for elders, the cognitive changes of aging, and lastly,
models of aging. In Chapter 3 the methods of data collection, a detailed description of the sample
participants, and an explanation of the instrument including validity and reliability results are
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provided. Next, Chapter 4 provided the findings of Chapter 3. Each research question was
addressed regarding age, sex, and race, and major findings were discussed.
Lastly, Chapter 5 provided the conclusions of the research and the implications for older
learners and educators. The impact of this study on the Needs Assessment and the
Implementation Phase of the generic Instructional Systems Design Model (ADDIE) was
discussed along with recommendations for program planning for older adult learning
environments. Innovative suggestions were also made for future research.
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Chapter 2: Literature Review
Chapter 2 is a review of the current research on the aging process and the impact of the
aging process on new learning and the acquisition of knowledge. Examined in Chapter 2 are the
constituents of successful aging, learning in older adulthood, distinctions of age, sex, and race in
relation to learning, an examination of learning style models, the relevance of educational
institutions and programs specifically for seniors, cognitive changes of the aging brain in relation
to learning, models of aging, and lastly, a short analysis of the Gregorc Learning Style
Delineator. Chapter 2 also provides an overview of the literature on senior living and factors that
affect older adults in learning environments. An understanding of the older adult’s life and
circumstances is crucial to an understanding of the rationale for this research.
Purpose of the Study
The purpose of this study was to identify the learning styles of older adults using the
Gregorc Learning Style Delineator. In this study, older adults were ages 65 to 75 years or over
75 years of age. This study also identified race (African American or Caucasian), and sex (male
or female) as additional variables. Data were collected from participants in university life-long
learning programs, an area agency on aging, and faith-based settings. This study sought to
ascertain the learning styles that were used by older learners or groups of older learners.
Learning style instruments, such as the Gregorc Learning Style Delineator, assist individuals in
building an awareness or identifying learning and teaching practices that are best suited to their
own cognitive abilities.
15
Research Questions
The following research questions were used in this study:
1. What are the learning styles of older adults in relation to age?
2. What are the learning styles of older adults in relation to sex?
3. What are the learning styles of older adults in relation to race?
Seniors in Later Years
Agism and the stereotypical concept of seniors as frail, infirm, helpless, isolated, and out-
of-touch has been redefined by the latest generation of older adults—the baby boomers. In fact,
many older Americans perceive their health as “excellent” as represented in Figure 2.1.
PERCENT
Figure 2.1 Percentage of Older Adults Who Rate Themselves as in Excellent Health
Source: Pew Research Center
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Today’s seniors want to enjoy an active and engaged retirement (Merriam & Kee, 2014)
that includes social activities, political involvement, physical sports, civic engagement, travel,
and a life balanced with time spent enjoying leisure activities and productive activities such as
part-time work, volunteerism, a new career, entrepreneurship (Franklin & Frick, 2008), and
completing or beginning a formal education (Dillon, Marini, & Miller, 2009). Learning new
information and education are key to maintaining active participation and creating a meaningful,
fulfilling life for our aging population.
Successful Aging
The concept of exactly what constitutes successful aging differs from theorist to theorist
and from one individual to another, depending on circumstances and personal characteristics or
life choices. An older adult’s concept of life and the aging process can affect the decision to
remain actively engaged or retreat into isolation and disengagement in the final stage of life.
According to Erik Erikson’s last stage of Erikson’s Life Stages: Integrity vs Despair (Erikson,
1997); If one has lived a fulfilled life and completed many of the goals and aspirations set out for
themselves, the final years are spent with integrity and dignity.
Conversely, if one lives with regret and remorse over poor decisions and outcomes,
despair is the result and older adults slip into sadness and isolation, and disengage from society
(Erikson, 1997). Erikson wrote his seminal work on the eight stages of life earlier in his career.
Once Erikson entered old-old age, in his 90s, he added another stage to his eight stages of
development—a ninth stage, one that he found himself experiencing personally. In the newly
developed ninth stage, hope and faith for further wisdom and enlightenment are named as the
syntonic quotient with no dystonic quotient mentioned as was the case in his previous life stages.
17
Erikson diverged from his model of positive versus negative developmental life stages and
envisioned the final stage of life as one of quiet reflection, with no adverse tasks or challenges to
overcome (Erikson, 1997). Other researchers and gerontologists, however, theorize old age
differently.
According to Rowe and Kahn (1998), “… successful aging consists of three factors:
avoidance of disease and disability, maintenance of high physical and cognitive functioning, and
sustained engagement in social and productive activities” (p. 133). Disease or disability may be
unavoidable, but maintaining physical and cognitive functioning, and staying active and engaged
is certainly under the control of every individual. In contrast, “…poor social connections,
infrequent participation in social activities, and social disengagement predict the risk of cognitive
decline in elderly individuals” (Zunzunegui, Alvarado, Del Ser, & Otero, 2003, p. 135). Indeed,
the role of active social engagement, be it in education, employment, volunteerism, cultural
activities, or religious institutions can reduce or eliminate the negative effects of aging on the
brain. Research by Goh and Park (2009), on neuroplasticity and cognitive aging revealed that,
“Cognitive engagement improves cognition. Social engagement is just as effective as cognitive
engagement [in improving cognition]” (p. 398). Engagement is key. The link between social,
cognitive, and physical activity with successful aging and a higher quality of life for seniors is
undoubtedly one of the most important social issues of the day.
Making the Decision to Learn
Numerous studies reveal that older adults are increasingly interested in formal and
informal educational programs (Danner, Danner, & Kuder, 1993; Pearse, 1991). Moreover, a
cognitive interest and a desire to learn are an older adult’s primary motivation to pursue new
18
learning experiences (Byrum & Seaman, 1993; Kim & Meriam, 2004; Scala, 1996; O’Connor
1987). Lin (2011) also found that older adults showed more interest than middle–aged adults in
experiencing formal and informal learning environments. Indicating that an older adult’s desire
to learn is more important than that of younger counterparts. In general, the motivating factors
for older adults to seek learning opportunities is personal growth and satisfaction (Lin, 2011),
improved self-esteem, to reduce the adverse effects of aging, and for social contact and
interaction (Graham & Donaldson, 1996; Kim & Merriam, 2004; & Little, 1995). Lin (2011),
using in-depth interviews, for more specific information, found five main reasons that adults
over 60 years of age were motivated to learn. First, a desire for knowledge, and the acquisition of
new information such as learning a new language or a new skill. Secondly, a desire for
stimulation, to exercise the mind, develop deeper understanding, and to be able to learn at a
higher level. Thirdly, a desire for self-fulfillment. Academic achievements are a credit to one’s
self-esteem and provide an inner status symbol. Next, a desire for generativity. The concept of
generativity is based on a need to pass on information to the next generation, by sharing and
passing on knowledge learned throughout a lifetime to younger learners. Generativity is the
major motivating factor in the desire to teach others. Lastly, new learning can be a transition to
another lifestyle or another career. Second careers are popular with today’s older adults and
many want to reinvent themselves in another field or a more meaningful occupation.
For older adults the impetus to seek new learning whether from a desire to reinvent
oneself and change one’s self-image and self-worth, or the need to make improvements or
changes in one’s life involves an internal redefining of identity and making value judgments that
will achieve a new self-view. A life altering event such as the death of a spouse, divorce, or
19
retirement can be the trigger that precludes these changes (Palazesi, Bower, & Schwartz, 2007).
New learning for these older learners could involve informal lessons or formal learning in a
community college or the attainment of a university degree commensurate with the new image,
but the initiation of new learning does not necessarily start as a response to internal angst or
external situations. Aslanian and Brickell (1980) reported that 83% of older adult learners
encounter a past, present, or future life event of either momentous or less significant proportions
that prompts new learning, and 56% of this group name career changes as the trigger that began
the process.
Many older learners see retirement as an opportunity to begin a new career in a field with
challenges and personal fulfilment, or to attain lifelong educational aspirations. Decisions can
now be made based on dreams of desire rather than that of need. In fact, as presented in Figure
2.2 the majority of seniors want to work compared to the few who actually need to work for
financial reasons. Moreover, older adults have the ability to instigate learning and direct the
learning process until the desired goals are met. These characteristics are integral components of
adult learning and differentiate adults from the pedagogical learning characteristics of children,
and therefore require different learning methods to engage the adult learner.
Other important characteristics of adult learners are the adult’s ability to be autonomous,
self-directed learners who can learn collaboratively with others. Self-directed learning is defined
by Knowles (1975) as, “A process in which individuals take the initiative with or without the
help of others in diagnosing their learning needs, formulating goals, identifying human and
material resources, selecting appropriate learning strategies, and evaluating learning outcomes”
(p. 23). Self-directed learning is any learning initiated by an individual based on self-determined
20
learning needs, and can take place individually with an instruction manual, or a self-help book,
or in a more formal setting such as college or university, the workplace, or in the community at a
community center, non-profit, faith-based, or other organization.
Figure 2.2 Rationale for Working in Retirement
Note: Asked only of those retirees who worked part time or full time, n=139.
Pew Research Center
The primary component of self-directed learning is that the learner takes the initiative to
pursue new learning and assumes responsibility for the tasks and exercises involved until the
completion of the learning experience. Furthermore, the realization by the individual that there is
a need to know certain information is critical in initiating the entire learning process. This
initiative has been described by Caffarella (1993) as a survival skill in response to the rapid pace
of change in modern society.
Our rapidly changing society has caused many seniors to rethink their role as retirees.
Social roles and life cycle phases indicate the way in which people view themselves and interact
21
with the world around them. Individuals have different roles as the life cycle revolves: parent,
partner, employee, caregiver, home-maker, and other roles relevant to each individual’s life
circumstances. The social developmental level of an individual runs concurrent with changing
social roles, during life, age, and, situations, and is responsible for personal growth and
development throughout life, as changes occur in the cognitive, emotional, physical, and
environmental aspects of life. One aspect of personal growth and development that does not
appear to change throughout the life cycle: the fact that people are lifelong learners. However, as
Ginsberg (2002) concludes, the current research “…provides no definitive answer as to learning
[styles] in the older years” (p. 42).
As lifelong learners, people seek learning experiences for intellectual stimulation,
community involvement, and a need for personal development, including one of the most
important motivators for new learning, the development of new job skills to achieve future career
goals (Cruse & Hillman, 2011). In fact, only 17% of the current generation of older adults plan to
stop working at the traditional retirement age of 65 years old. Many plan to continue working to
supplement their income, or for benefits included in a job package, such as health insurance or a
pension fund, but many are retraining for second careers or advancement in a current career.
Additionally, 33% of adults aged 55 to 79 years of age participate in formal learning such as,
credentialing programs, work related courses, or courses of personal interest, and 69% are
involved in informal learning such as club or group activities, and attending work related
conferences or conventions. Age also has an influence on the decision to pursue an education
related to work skills development. Twenty-six percent of 55 year olds take classes for
employment related skills compared to 13% of 70 year-olds (Cruse & Hillman, 2009). With so
22
many senior citizens motivated to learn, the number of obstacles to overcome to achieve
educational goals can be overwhelming. Some barriers are self-imposed, and some are due to
ageism, and the stereotypes that exist in our society.
Learning Style Models
There are many types of learning style assessments, most of which are directed towards
young students in a classroom setting. Learning style assessments of adult learners are often
performed in higher education or workplace situations. However, adult assessments can be of
value in any adult population though results are often contradictory. For instance, as reported in
Truluck and Courtenay (1999), using the Gregorc Learning Style Delineator, Davenport’s (1986)
investigation of learning style preferences of a group of Elderhostel participants found gender to
be a significant factor in learning style preferences, but the age differences were not considered
significant. In contrast to Davenport’s (1986) research, Delargy (1991) using Kolb’s Learning
Style Inventory, found age to be a significant factor in learning style preferences between
younger adults and adults 55 years of age and older. This current research using the Gregorc
Learning Style Delineator found neither age nor gender to be significant. The discrepancies
continue, and criticisms of every learning style model exist, each with proponents and detractors.
Kolb’s Learning Style Inventory
Kolb first developed the Learning Style Inventory (LSI) in 1971. The instrument has
undergone several revisions until the current version, the LSI3 was developed in 2000. The
instrument is a 12 sentence completion, rank-ordered, questionnaire that results in four learning
styles: diverging, assimilating, converging, and accommodating (Ginsberg, 2002). Described by
Kolb (2000) as experiences translated into concepts which are then used as guides in the choice
23
of new experiences. New learning consists of four stages which are Immediate/Concrete
Experiences—the basis for observation and reflection. Observations/Reflections are then
assimilated into a Concept from which new implications for action can be drawn and lastly, the
new implications serve as guides for new experiences (Ginsberg, 2002).
To be effective, learners must be able to demonstrate learning abilities as follows:
Concrete Experience—fully involve themselves in new experiences
Reflective Observation—reflect on experiences from different perspectives
Abstract Conceptualization—create concepts that integrate observations into theories
Active Experimentation—use the new theories to problem solve and make decisions
Ginsberg (2002) using Kolb’s LSI3 found no differences between sample participants
who were young/old (65 to 74 years of age) and old/old (75 to 99 years of age). All participants
were Caucasian and were divided by sex, age, and marital status. Ginsberg (2002) also found that
all participants preferred either the diverging or assimilating learning style and concurred with
Kolb’s (2000) assessment that learning styles do not change as individuals move from young/old
to old/old.
Felder and Silverman’s Learning Style Model
In an analysis of learning style models, Platsidou and Metallidou (2009) describe Felder
and Silverman’s Learning Style Model as categorizing an individual’s learning style preference
by type and mode of perceiving new information: sensory or intuitive; verbal or visual, in
processing new information: inductive or deductive; active or reflective, and in the rate that
information is understood: sequential or global. Using this information, individuals are then
24
classified into one or the opposite pole of the following four styles: sensing or intuitive, visual or
verbal, active or reflective, sequential or global.
The unique aspect of the Felder and Silverman’s model is that the dichotomous learning
style dimensions are on a continuum and not set as one dominant learning style. The learner’s
score on each construct may be strong, moderate, or mild, and may change with time or situation
(Platsidou, & Metallidou, 2009). This feature demonstrates learner flexibility depending on
learning circumstances in much the same manner as the Gregorc Learning Style Delineator
reveals a dominant learning style followed by a secondary style and two less developed learning
styles. The dominant learning style is often closely followed by a secondary style and learners
often exhibit two equally dominant learning styles as was the case in this research with 13 of 101
participants displaying two equally dominant learning styles. Flexibility and the ability to utilize
different learning modalities to solve novel problems and accomplish difficult tasks could be the
reason that learning style tests encounter difficulty in definitively identifying one single learning
style within an individual or groups of individuals.
Barriers to Learning
Education Equals More Education
Whether new learning is sought out for practical reasons or for personal enhancement the
relationship between previous educational attainment and the decision to seek new learning
opportunities increases commensurately. Cruce and Hillman (2009) estimated that only 7% of
older adults with an eighth grade education pursue formal learning, compared to 11% with a high
school education, 14% with an associate degree, 17% with a bachelor’s degree, 20% with a
master’s degree and 29% with a doctorate. The lower educational rates for certain seniors appear
25
to reflect a racial component. Figure 2.3 represents the older population’s educational attainment
of a bachelor’s degree by race and Figure 2.4 presents the older population’s attainment of an
associate’s degree by race. Outreach programs targeting seniors with low levels of education
would encompass a group usually marginalized by traditional educational institutions, yet this
group is in need of a fully engaged meaningful retirement as much as their more highly educated
counterparts, and efforts to recruit these undereducated seniors should be of primary concern to
both formal and informal institutions of education.
26
Figure 2.3 Older Population with Bachelor’s Degree by Race
Adapted from the U.S. Census Bureau 2006
Figure 2.4 Older Population with an Associate’s Degree by Race
Adapted from the U.S. Census Bureau 2006
27
Agism
Agism is also a barrier to educational opportunities for seniors. Agism is any attitude,
action, or institutional structure that subordinates a person or group because of age or any role in
society, such as retirement, purely on the basis of age (Woolf, 1998). As an “ism,” agism reflects
a prejudice in our society against older adults. Although federal laws protect workers from age
discrimination in the work place, agism still exists in many segments of our society (Larkin, et
al. 2007). Older people are also stereotyped and considered of little value, a burden, slow to
accept change, economically and physically dependent, deaf, in poor health, politically
conservative, alienated, nonsexual, and living alone (Coudin, & Alexopoulos, 2010). In fact,
lifestyle choices including cognitive training, higher education, physical activity, and social
interactions have been shown to prevent memory and cognition declines and, “The belief that all
memory seriously declines with age is just an agist stereotype that is contrary to the facts”
(Palmore, Branch, & Harris, 2005, p. 225). Palmore et al. (2005), further stated that knowledge
about the facts of aging can reduce negative stereotypes and prejudices against elders.
The Digital Age
Most classes today require computer access, so a certain degree of technological skills are
necessary before an older learner can enter most learning environments. Educational outreach
has progressively reached many of the computer illiterate older generation and some have
embraced technology; however, a lack of accessibility, has still left some older learners out of
the computer age (Sargant, 1997). Not only do some older learners face a lack of technological
skills, but physical problems also limit an older learner’s ability to successfully engage in
learning opportunities. Many common health problems that affect an older adult’s decision to
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engage in new learning include a decrease in vision and hearing, immobility, heart conditions,
and arthritis (Coudin & Alexopoulos, 2012).
Transportation
Transportation is another issue that older learners who can no longer drive must
overcome. Automobile accidents are the second leading cause of accidental death among seniors
over 65 years of age, and there is little doubt that visual acuity and hand-eye coordination
account for a senior’s ability to safely operate a motor vehicle (Palmore et al., 2005). The loss of
the ability to drive and be mobile in a society that depends on transportation to exist is a major
debilitating factor in the life of an older adult. Alternate modes of transportation must be made
available for continued participation in an active lifestyle. Isolation and the cognitive decline
associated with a lack of social interaction, access to resources, and access to educational
opportunities contribute to unhealthy aging and a dependency on social services at tax payer
expense (Taylor, Morin, Parker, Cohn, & Wang, 2009).
Seniors in Rural Areas
Another educationally underserved population of seniors are those in rural areas.
Location is a major factor in an older learner’s decision to pursue educational activities with
proximity to home a convenience that increases attendance. Only 7% of older adults in rural
areas participate in new learning opportunities compared to 14% of their counterparts in urban
and suburban settings (Cruce & Hillman, 2009). For African Americans in rural areas the
statistics are even lower. The National Center for Education Statistics (1978), reported that less
than 2% of elderly African Americans were involved in adult education programs. Using a factor
analytic approach researchers Darkenwald and Valentine (1985), and Scanlan and Darkenwald
29
(1984), identified six deterrents as to why elderly African Americans do not participate in
educational programs: lack of confidence, lack of course relevance, time constraints, low
personal priority, cost, and personal problems. A similar rationale has been found by other
researchers. Borthwick (1983), found cost, inconvenience, transportation problems, and attitude
towards self, education, and educational institutions as major deterrents. Spence (1997) also
mentioned an issue not common in the literature—embarrassment. Individuals unable to read or
write or with problems reading and writing, may not want to expose these vulnerabilities.
Access is problematic, but the number and variety of classes now offered on-line could
bring geographically isolated older learners into the realm of higher education, and provide a
degree of socialization and interaction for these seniors while contributing to the need for
lifelong learning and a more satisfying retirement.
Older Women and Men in Education
In 1970 only 6% of women over 55 years of age held a bachelor’s degree (US Census
Bureau, 1970), but by 2006, 25% of women 55 to 64 years of age, and 15% of women over 65
years of age held a bachelor’s degree (US Census Bureau, 2006). However, educational levels
for both sexes are increasing incrementally as men in the 55 and older age group in 1970 also
had an extremely low graduation rate for bachelor’s degrees at 9% (US Census Bureau, 1970),
compared to a 29% graduation rate for bachelor’s degrees in 2006. (US Census Bureau, 2006).
Conversely, more associate degrees are held by older women than older men. In the 55 to 64-
year-old age group 8% of women and only 6% of men hold associate degrees. In the 65 and
older age group, there is an even wider margin of 10% women and only 7% of men holding
30
associate degrees (US Census Bureau, 2006). The discrepancies in education between women
and men, also, apply to the workforce.
Older Women and Men in the Workplace
Women have historically outlived men, and as the population ages the larger portion of
older adult learners will be women. The average life span for women in the United States in
1998, was 79.2 compared to 73.6 for men (US Census Bureau, 1999). Although women outlive
men, older adults in the workforce are predominately men. In 2004, 70% of the men aged 55 to
64 were in the workforce, but only 57% of the women in the same age group were working.
Although the number of women 55 to 64 years old in the workforce is lower than men of the
same age group, the number of older women working is double that of the older women working
in 1950. In the 65 and older age group 19% of men compared to 12% of women were still
working (US Census Bureau, 1999). Figure 2.5 is a comparison between men and women in the
workforce in 1950 and in 2004.
The substantial increase in working women is due in part to women who stayed in or
returned to the work place because of the higher divorce rate today, or because of the increased
longevity of women (US Census Bureau, 2004). With the increase of senior adults staying in the
workforce concerns about discrimination and agism persist. As one older student at a community
college explained, “Finding employment will be the biggest problem after I graduate…because
of my age. There is a lot of discrimination against women my age in the workforce” (Larkin, et
al., 2007, p. 16). Apparently these concerns are valid. The poverty rate in elderly women at
11.8% is almost twice that of elderly men at 6.9%. Of elderly single women including single
31
African American women 3.8% live in poverty compared to 10.6% of elderly married women of
both races.
Figure 2.5 Older Men and Women in the Workplace 1950 and 2004
Adapted from Fullerton, 1999 (1950 statistics) and US Census Bureau, 2004.
Of all elderly single Caucasian women 10.3% live in poverty and 26.4% of all elderly
single African American women live in poverty (Zhan & Pandey, 2002). There are many reasons
that older women are more likely than older men to live in poverty. According to Zhan and
Pandey (2002), women in general spend less time in the workforce compared to men, due to
child bearing and child rearing responsibilities. Thus, retirement benefits that are linked to
employment are decreased for women. However, women with a post-secondary education are
economically more self-sufficient and independent throughout their lives which is especially
important in the retirement years. Better educated women are more likely to be paid higher
32
wages, be in more stable employment, and contribute more to pension plans (Henderson &
Ottinger, 1985; Hudson, 1984; Leon, 1985). Less economic stability in retirement for women of
a low educational level will compel these women to seek opportunities to enhance skills and
marketability through educational endeavors that can place them in better paying jobs and
provide needed income during retirement.
Unfortunately, employers are slow to adapt and accommodate older workers and continue
to believe outdated notions and negative stereotypes (American Association for Retired People,
2006), leaving older workers few options. One viable option available to older adults who want
to continue to work is to start their own business. One in five older workers is self-employed and
one-third of these entrepreneurs started a new business at the age of 50 or older (American
Association for Retired People, 2007). There is an increasing trend in the number of individuals
55 to 64 years old who are willing to take risks and pursue entrepreneurial endeavors during
retirement years (American Association for Retired People, 2004). As presented in Figure 2.6
seniors have diverse employment related plans after retirement, and Figure 2.7 illustrates the
percentages of seniors still in the workforce, especially the 55 to 64-year-old age group that does
not yet qualify for federal retirement benefits.
33
Figure 2.6 Plans to Work in Retirement
Adapted from Metlife Foundation/Civic Ventures New Work Survey 2005
Figure 2.7 Workforce Participation Rates Among the Older Adult Population
Adapted from AARP, 2006
34
Older African Americans and Caucasians in Education
The number of older African Americans in attendance at institutions of higher education
is increasing and will continue to do so as the peak of the current population wave reaches
maturity. In 2004 approximately 9% of the 55 to 79 year-old group was composed of African
Americans. By 2050 African Americans will constitute about 14% of this same age group (US
Census Bureau, 2004). Comparably, the number of Caucasian Americans in the 55 to 79 age
group will increase in numbers, but by 2050 Caucasian Americans will only be 57% of the 55 to
79 year olds--down from 81% in 2004 (US Census Bureau, 2004) In 2006 only 14% of African
Americans 55 to 64 years of age earned a bachelor’s degree, and only 11% of the age group of
African Americans 65 and older had a bachelor’s degree, compared to Caucasian Americans at
26% and 21% respectively. African Americans and Caucasian Americans over 55 years of age
hold Associates Degrees at approximately the same rate: 6% and 7% respectively. At the high
school level 86% of Caucasian Americans and 66% of African Americans in the 55 to 64-year-
old age bracket graduated from high school, and in the 65-year-old and older group 80% of
Caucasian Americans and 55% of African Americans held a high school diploma (US Census
Bureau, 2006).
Older African American Women in Education
Older African American women face more obstacles in the pursuit of education and
employment than any other segment of the senior population. Low education levels combined
with low expectations of their ability to earn a living wage leaves older African American
women especially vulnerable to the conditions of poverty, and therefore an impoverished
retirement. Jones (2007), of The National Caucus and Center on Black Aged, described the
35
plight of domestic workers who still need to work after age 65, but can no longer perform
physically demanding labor—leaving these workers with limited options. Even entry level jobs
in health care or customer service require training and computer skills, but with lower education
levels across the lifespan, it is unlikely that older African American women will have the
confidence to return to an educational setting. A concerted outreach effort will be required to
reach this underserved and marginalized segment of older learners.
In contrast, older African Americans in general, are more likely than older Caucasian
Americans, at 63% and 47% respectively, to seek career changes that provide more meaningful
employment (Larkin et al., 2007). A fulfilling job in the retirement years is even more important
to seniors who, after a lifetime of experiences and knowledge, want an opportunity to give back,
and leave a legacy for future generations (Kassab, 2011), but for seniors of low income, the cost
of education or re-training can present a problem.
Prohibitive Costs
Price is another consideration that senior learners take into account when making the
decision to pursue new learning--formal or informal. With older adults living on a limited fixed
income, discounted or cost-free classes would enable more seniors to engage in formal
education, and a few states agree, some to a lesser extent, but almost all states offer some form of
incentives or other discounts for older students. Twenty-two states provide full tuition waivers to
accommodate senior students returning to school, but most of these come with restrictions and
limitations such as audit only, or non-credit classes. A few states restrict the field that an older
learner can enter, or the type of institution that can be attended, and some states offer tuition
waivers only to senior citizens of low income. Ten states offer discounts of up to 50% on tuition
36
but again, restrictions apply. The age restriction is one limitation that applies in every state, but
the age limit differs from state to state. Eight states require an older learner to be at least 65
years old, and 15 states allow waivers at 60, but California alone allows older students to be
eligible for tuition waivers starting at 50 years of age (A Senior Citizen Guide for College,
2016).
Most states have statutes requiring institutions of higher education to offer tuition waivers
and discounts to older citizens, but seven states leave the decision to the discretion of each
school’s administration, and two states have no provisions for older learners at all, but ten states
offer full tuition waivers with no limitations or restrictions except that of age. Alabama is not one
of those states. Alabama offers older students, at least 60 years of age, a full tuition waiver at any
of the state’s 24 two-year post-secondary schools (A Senior Citizen Guide for College, 2016).
Universities are not included in Alabama’s senior citizen tuition waiver, but trade, technical, and
community colleges offering two-year associates degrees are, and credits earned at these
institutions at no cost can be transferred to universities offering four-year bachelor’s and
graduate degrees. The cost of a bachelor’s degree, though not tuition free, would be substantially
reduced for Alabama’s older citizens.
Activities of Successful Aging
Working in the Later Years
As this new generation of senior citizens redefines retirement, even the word,
“retirement” has fallen out of favor and been replaced by the term, “The Third Age” (Laslett,
1998). The Third Age is described as occurring when individuals leave the workforce and
become free to pursue personal ambitions and desires. Contrary to this picture of The Third Age,
37
many older adults plan to continue working and not necessarily for financial reasons. Figure 2.8
presents the percentage of seniors who continue to work well past traditional retirement age. In a
study by the Pew Research Center: Social and Demographic Trends Report (Taylor, Morin,
Parker, Cohn, & Wang, 2009), of those over 65 years of age 69% have a part-time or full-time
job because of a desire to work, not because income is needed. Only 16% claim to work for
financial reasons. In fact, 31% of working adults 65 and older plan to never stop working, and
another 27% are undecided about ever leaving the workforce and retiring. Eleven percent claim
to still be in the work force even though not all have jobs. The Social and Demographic Trends
Report by The Pew Research Center (Taylor, et al., 2009), conducted nationwide, included 1,332
individuals who were 65 years old and older, and revealed some conflicting reports on what it
actually means to be retired from work.
…retirement means different things to different people. Some 8% of adults
ages 65 and older say they are retired but working part-time; 2% say they are
retired but working full-time; and 3% say they are retired but looking for work.
Most of these retirees who are still in the workforce say the main reason they
continue to work is that they want to, not because they need the paycheck.
(p. 9)
The demarcation between work and retirement has become a nebulous concept at best,
and can only be determined by each individual retiree, according to a personal definition. The
classic definition of a retiree who no longer works, no longer applies.
38
Figure 21.8 Percentage of Retirement by Age
Note: based only on those who say they are retired. Pew Research Center
The ambiguity that older adults feel towards the relationship between retirement and
work may, in part, be due to the perception that older adults have towards their chronological
age. According to Taylor, et al., (2009), in the Pew Research Center’s Report on Social and
Demographic Trends; of adults aged 65 and older, 60% claim to feel younger than their
chronological age, while 32% said they feel the same as their calendar age, and only 3% said
they feel older than their chronological age. As presented in Figure 2.9 the difference between
the calendar age and the age an individual actually feels increases as age progresses.
39
Figure 2.9 Difference Between How Old We Feel vs Actual Age
Note: Asked of all 2,969 adults in the survey. Pew Research Center
Seniors 50 to 64 years of age report feeling at least 10 years younger than their
chronological age, but of the individuals aged 65 to 74 one-third said they feel 10 to 19 years
younger than their chronological age, and one in six said they feel 20 years younger than their
actual age. Of the study participants 65 to 74 years of age only 21% said they feel old, and of
those participants 75 and older only 35% said they feel old, leaving 61%, the majority of the
oldest seniors, saying they do not feel old. Figure 2.10 presents the large number of seniors who
feel younger than their chronological age compared to those who feel their chronological age and
the relatively few who actually feel older than their calendar age (Taylor, et al., 2009).
This phenomenon is consistent across age groups in the Pew Research Center’s Report:
Half of all adults said they feel younger than their actual age, with only 9% who said they feel
older than their actual age, and 38% who said they feel their chronological age (Taylor, et al.,
40
2009). These findings could explain why older adults want new challenges and experiences late
in life, and why seniors want to forgo the stereotypical life of leisure that is a common
misconception of retirement.
Figure 2.10 Percentage Feeling Younger, Older, or the Same as Actual Age
Note: “Don’t Know/Refused” responses not shown. Adapted from the Pew Research Center
If older adults perceive themselves as 10 to 19 years younger than they actually are, age
would not be a deterrent in the pursuit of long held dreams and aspirations, such as a formal
education, a new career, entrepreneurship, a new life skill, hobby, or sport. The possibilities are
endless, but almost all dreams and aspirations require new learning, and educators as well as
educational institutions must be prepared to meet the challenges that older and elderly adult
learners will create in learning environments.
Volunteerism - Giving Back
Especially appealing to many professionals from fields outside education is K-12
education. According to a 2005 survey, 20% of the 35,000 people who took alternative teaching
41
certification programs were 50 years old and older (Foster, 2010). Retired science, technology,
engineering, and mathematics, (STEM), professionals from outside education are eager to give
back by helping to develop the next generation of the STEM workforce while combining a
passion for their field with additional income (Foster, 2011). The concept of “giving back” to
society in later years after a wealth of knowledge and expertise is acquired, is especially popular
with seniors who now have time to contribute in fulfilling and creative second careers.
Entrepreneurship
A second career is the term used for any career taken up after an initial career, but Encore
Careers is a non-profit philanthropic organization that funds entrepreneurship for seniors over 60
years of age. At Encore Careers new enterprises must have a social impact in areas of public
interest, such as education, the environment, health, the government sector, social service, or
non-profits. Encore Fellowships transition experienced professionals from the corporate sector
to the social sector and allow older adults to find fulfilling work that combines personal values
and interests with meaning and income, while “giving back” and having a chance to leave a
legacy. One Encore sponsored organization employed Native Americans over 50 years of age to
teach their native language to children. Another Encore organization teaches environmentally
sound farming practices, and another assists the disabled elderly to remain independent at home
(Kassab, 2012).
Marc Freedman, founder of Encore Careers, names Al Gore as an example of the
capacity people have to reinvent themselves in later years, “…Gore found himself by losing
himself…and being liberated from ambition, the idea that there’s a particular ladder you have to
scurry up and if you don’t make it to the top it’s all over. Essentially he found a different ladder”
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(Goodman, 2007, p. A.17). After losing the presidential nomination in 2000, Al Gore became an
advocate against global warming and won a Nobel Peace Prize in 2007. Gore also went on to win
a Grammy Award, an Emmy Award, an Academy Award and wrote a best-selling book, An
Inconvenient Truth (nobelprize.org). The analogy of finding a different ladder is one that
resonates with many older Americans. Research conducted for Encore Careers revealed that as
many as nine million Americans aged 44 to 70 years old are already in second careers, and half
of the nine million not already in second careers are interested in another occupation for the
retirement years (Berland, 2011). Freedman built the concept of Encore Careers to fit the longer
lifespans and circumstances of the 21st century’s older adults. Freedman’s vision also aligns
with the value systems of the current cohort of elders who have successfully created social
change through advocacy and awareness in younger years, and created a lasting impact on
society that still exists today. Freedman also notes, “The U.S. will need experienced seniors as
it…faces labor shortages in such critical areas as education and health care” (Franklin & Frick,
2008, p. 30) and the US Department of Labor (2006) reiterates this claim, stating that in 2016 the
U.S. will have 47% more workers who are 55 and older than in 2006, a prediction that will
increase the growth rate for seniors to five times the projected growth rate for the overall work
force (Franklin, & Frick, 2008).
Formal Education in Later Years
Older adults today are an extremely diverse group (Bjorklund, 2011; Findsen & Formosa,
2011), so there are many reasons that seniors would pursue an education in later years: personal
growth and development, academic interests (Perkins, & Robertson-Tchabo, 1981), intellectual
stimulation (Kingston, 1982), and the desire to learn something new (Romanuik & Romanuik,
43
1982). In other words, learning for learnings sake. As presented in Figure 2.11 seniors participate
in education for many reasons other than the attainment of a formal education. However, the
completion of an academic degree or learning a new skill can fulfill lifelong aspirations of a
career in a certain field, and many seniors want to update or learn new skills to stay current or
make a late life career change (Dillon, Martini, & Miller, 2008). Formal education does not
necessarily mean a commitment to an intense four-year bachelor’s degree. Certificate level
programs include certificates in information technology, health care, teaching, and other service
professions which are available at local community colleges and can be completed in as little as
six months, thereby preparing seniors for civic, volunteer, or employment opportunities (Dillon,
et al., 2008).
Figure 2.11 Education Participation Among Older Adults
Adapted from the U.S. Department of Education, National Center of Education Statistics, 2007.
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A Successful College Transition
One north-eastern community college that has successfully integrated older learners into
the school’s strategic planning and sustainability has done so with a $3.2 million grant from the
American Association of Community Colleges. This school has taken advantage of the
availability of local resources and creatively constructed programs specifically aimed at older
learners. Called the Plus 50 Initiative, matches with community, civic, and service opportunities
were made by gathering focus groups and surveys of local community seniors to identify the
talents and experiences of the older population. The school then offered specific courses,
programs, services, and job training that the seniors needed--creating an advantageous situation
for both the school and the seniors (Dillon, et al., 2008).
However, many extenuating factors were responsible for the success of the Plus 50
program, some incidental, and some more purposeful and challenging. One of the most
instrumental reasons for the success of the program was the demographics of the county that the
college serves. Twenty-three percent of the workforce was 55 years old or older, compared to
the national rate of 3.5%, and 60% of the households in the county include at least one adult over
the age of 55, which is double the national average (Smith, & Sheffield, 2003), leading college
president Kathleen Schatzberg to predict, “…we look like the rest of the nation will look in 15
years” (Dillion et al., 2008, p. 44).
The college also sought out input from community leaders, and advocates for older
adults. A strategic approach to recruiting students over 50 years of age targeted older workers
who were in transition back to employment, and wanted to update skills in information
technology, make career changes, earn a certificate, or begin a degree. As a result, short-term
45
flexible credit programs were developed specifically for adults who wanted to return to paid
employment, and advising services for these seniors in transition was created by the student
affairs department. Sustaining the new initiative also required a commitment from the entire
campus staff: the president, faculty, and administration, plus workforce development leaders,
human services leaders, and advocates for elders in the community. Plus 50 learners were
incorporated into the enrollment management program, and the orientation process which was
developed with the assistance of representatives from the Plus 50 learners who were also on
college advisory boards, and committees as Plus 50 advocates. An age–appropriate curriculum
was developed by faculty members to stress andragogical principles, and older adult learning
styles, with stipends for faculty who integrated Plus 50 perspectives into their classes. A public
relations officer, conveyed the school’s commitment to older learners through proactive
newsletters, senior events, success stories, outcomes, and public awareness presentations in the
community (Dillon et al., 2008). The sustainability of the Plus 50 program was achieved through
a commitment to the mission, strategic planning, a campus paradigm shift, structural and
procedural improvements, and a message that welcomed older learners back to school.
Lifelong Learning Institutes
Another avenue of education for seniors, in a less formal environment, exists in lifelong
learning institutes. As longevity in the United States increased during the 20th century, from 47
years in 1900 to 84 years in 2012, the number of Americans over the age of 65 also increased,
from 3 million to 40 million, respectively (Shinagel, 2012). Other industrialized nations of the
world experienced the same demographic shift. The changing demographics and compulsory
retirement in industrialized nations left many older adults worldwide searching for productive
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activities rather than a retirement spent in isolation and boredom (Shinagel, 2012). As policy
makers and health care providers became aware of the vital connection between well-being and
physical and mental decline in elders, education became crucial in keeping older adults active
and engaged, thereby delaying the tax burden of large numbers dependent elderly citizens
(Shinagel, 2012).
Institutions of lifelong learning, specifically for older learners, were first established in
France in 1968 and relied upon a close connection to universities. The focus was on academic
subjects with university teachers, teaching in university classrooms, and all at no cost to elders.
Another version of lifelong learning institutes, established in Britain in 1981, was based on a
more informal model, with members paying a small fee, and class subjects chosen and taught by
peers, often in the homes of other members. (Villar, & Celdran, 2012). Under either the French
or British model, both are now known collectively as Universities of The Third Age, or U3As,
and both maintain goals of raising the level of physical, mental, social, health, and quality of life
for elders (AIUTA, 2006). The success of U3As has spread to five continents, and now includes
820 separate sites and 300,000 members with a Virtual University of The Third Age launched in
2009 for isolated or homebound learners who lack involvement and a sense of community so
vital to healthy aging (VU3A, 2012).
In the United States, the Bernard Osher Foundation founded the Osher Lifelong Learning
Institutions, known as OLLI, in 1977. Like the French model of U3As, each site is associated
with a college or university for support and volunteer leadership (Shinagel, 2012). OLLIs offer
non-credit courses of interest to seniors aged 50 and older and are supported and administrated
by member volunteers similar to the British model. Classes include a wide variety of topics such
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as the sciences, foreign languages, hobbies, and physical fitness (Osher Lifelong Learning
Institute, 2015). Classes support the needs and preferences of older learners which include the
application of andralogical principles espoused by adult educators and supported by evidenced
based research. The local Auburn OLLI also offers university library privileges, an opportunity
to audit university credit classes, and discounts for membership in the Alumni Association,
university bookstore, and university event tickets (Osher Lifelong Learning Institute at Auburn
University, 2015).
The success of lifelong learning institutions in keeping older learners active and engaged
is undeniable. Formosa (2010), reported that in a 2006 survey conducted by the International
Association of Universities of the Third Age, the participants were motivated to join an
institution of lifetime learning for two main reasons: to learn new knowledge (41%), and to make
social contacts (38%); however, after joining the members reported an increase in friendships
(15%), personal satisfaction (9%), self-awareness (4%), social involvement (5%), and acquiring
new knowledge (17%) thus adding unanticipated benefits to the learning experience.
Also, for seniors over 50 years of age in the United States, Legacy Leadership Institutes
provide 45 to 65 hours of class room training in civic engagement followed by an internship of
200 to 450 hours in a community organization. Students are then expected to become involved in
a non-profit organization on a paid or unpaid basis (Villar, & Celdran, 2012), creating benefits
for the individual, the organization, and the community.
Another venue for older adults is Elderhostel which originated in the United States in
1975 (Shinagel, 2012), and has now spread worldwide. Also administrated by volunteers,
Elderhostel, recently renamed Road Scholars, offers seniors a liberal arts education, with support
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from an affiliation with a university through educational travel with peers, which also provides
the essential social component conducive to older learning (Chen, Kim, Moon, & Merriam,
2008). According to Brady (1983), the typical Road Scholar is educated, middle-income, over
60 years of age, and in relatively good health. Chen et al. (2008), further called attention to the
homogeneity of the participants in OLLI programs as predominantly Caucasian, educated,
middle class, men and women, although women usually outnumber men. Formosa (2010),
reports that most OLLI programs offer a limited selection of courses of interest to men, however;
a review of local OLLI class selections indicated a broad range of diverse topics in Liberal Arts:
literature, science, history, languages, and personal development: painting, cooking, gardening,
and fitness (OLLI, Auburn, 2015). The classes offered by OLLI are not gender specific, indeed
the assumption by Formosa (2010), that men would be interested in topics that would not be of
interest to women is gender-biased and outdated. The fact that women outlive, and therefore out
number older men is more likely to account for the larger number of older women engaged in
OLLI activities (Taylor, et al., 2009).
Also, older learners are segregated from younger adults at U3As and Lifelong Learning
Institutes. Elderly learners are interested in the same educational programs as younger students,
though for different reasons, and should therefore be integrated into the same educational
classes. Intergenerational contact also benefits both generations by reducing stereotypes about
older adults, improving social skills for younger adults, and increasing the self-worth of both
generations (Villar & Celdran, 2012). In fact, gender, and age are not the only inequity in
lifelong learning institutions. A lack of diversity in general is also evident. Peers of lower
educational and socio-economic levels, ethnic backgrounds, and frail physically dependent older
49
learners are overlooked (Formosa, 2010). Yet, the concept and rationale of lifelong learning also
applies to elders of diverse backgrounds: social engagement and learning opportunities reduces
dependency on community resources and the concomitant costs to tax payers. Equal rights to
learning opportunities requires learning institutions to make a concerted outreach effort to the
marginalized members of the senior population.
Cognitive Changes in Older Adults
The Aging Brain
As normal healthy older adults experience a decrease in eyesight, hearing, and physical
strength, so too does the brain undergo changes in mental processing. The loss of two percent of
white matter per year throughout the brain begins at age 30 and causes the brain to lose both
weight and volume. Other structural changes that contribute to cognitive changes in the cyto-
architecture of the aging brain include vascular decreases in blood flow and a decrease in neuro-
chemical-transmitters and the synapses (connections) used by the transmitters for neural
processing (Crossley, 2008). The aging process includes a normal, gradual decrease of cognitive
function in healthy adults, including processing speed, in which response time and time on tasks
is slower (Salthouse, 1996), working memory, which is the retrieval of information in temporary
storage (Baddeley, & Hitch, 1974), and executive functions, which are important for the higher
cognitive processing involved in reasoning, and the ability to plan, monitor, activate, and
manipulate new information (Cicerone, 2006). Long term memory, known as episodic memory,
and short term memory, known as working memory, together have the largest effect on cognitive
decline because memory is affected by other processes including the speed of retrieval and
higher level executive functions. Memory decline leaves older adults with problems
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remembering new information, retrieving previously learned information, such as names, and
experiencing word finding problems, such as having difficulty remembering even common
words (Zelinski et al., 2011).
Improving Cognitive Decline
Certain areas of the brain are particularly sensitive to age related changes. Correlations
between age and cognitive changes in the brain such as reasoning, spatial visualization, episodic
memory, and speed of information processing, are associated with these areas. However,
vocabulary and language based functions remain intact (Kaszniak, & Newman, 2000). The
forebrain and prefrontal cortex is especially vulnerable to normal age related changes, although
individual differences do occur and certain individuals appear to be resilient to these normal age
related changes (Woods, & Clare, 2008). Evidence exists that cognitive decline, though not
completely preventable, can be reduced or even improved through a multi-faceted theoretically
based cognition rehabilitation program for older adults experiencing normal cognitive decline
(Zelinski, 2009), and indications are that these interventions can produce enduring improvements
in memory, and performance (Winocur, Craik, & Levine, 2007), meaning that participation in
new learning and educational programs can have lasting effects on memory improvement.
Studies of the use of cognitive training strategies in executive processing and speed, have
demonstrated a transfer of improved cognitive skills to untrained activities (Zelinski, 2009),
indicating the brain’s ability to activate additional sites for neuro-cognition thus, improving
cognition when applied to new activities. Also, neuroimaging has revealed increased neural
activity in key frontal regions of the brain, which are associated with executive functioning, after
participants performed cardio vascular training, indicating that increased blood flow to the brain
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from physical exercise, increases neural activity. Increased blood flow also helps to reduce brain
shrinkage and maintain brain volume (Hertzog, 2009).
In addition, studies into the cognitive benefit of social networks, group cognitive
activities, civic engagement, and other social activities that engage seniors, reveal less cognitive
decline than in uninvolved older adults (Zelinski et al., 2011), indicating that socializing
improves cognition. Furthermore, much of the current research on the aging brain and cognitive
function, discuss the protective effects of higher education in maintaining levels of cognitive
performance (Stern, 2006). According to Stern (2006), higher educational levels are used as an
index of cognitive reserves that can compensate for, or be protective of, normal cognitive
decline. Whether higher education levels act as a reserve supply of cognitive functions, or as
protection against cognitive decline is still uncertain, but the general consensus among
researchers is that higher education levels in individuals equals slower cognitive decline in later
years.
Neuro-Plasticity
According to Goh and Park (2009), the aging brain has the ability to expand activity by
recruiting additional sites of activation in response to the effects of cognitive decline associated
with advanced age, such as decreased blood circulation which causes brain shrinkage and a
decrease in the number of neurotransmitters which are the chemical impulses that the brain uses
for communication between brain cells which are known as neurons. Synaptic sites on each
neuron then receive and transmit the neurotransmitters to the next neuron thus increasing
activation sites for neural expansion and cognition. Known as neuro-plasticity, this recruitment
of additional sites of activation can enable the aging brain to compensate for structural and
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neurobiological decline. The two most important structural changes in the aging brain are
reductions in brain volume, and cerebral cortical thickness, both caused by a loss of neurons. The
cerebral cortex, also known as grey matter, is a dense layer of neurons that covers the prefrontal
and frontal cortex and is responsible for higher executive level thinking such as memory,
reasoning, and problem solving (Davatzikos, & Resnick, 2002; Head, Buckner, Shimony,
Williams, Akbudak, & Conturo, 2004; Moseley, 2002; Raz, Lindenberger, Rodrigue, Kennedy,
Head, & Williamson, 2005; Resnick, Pham, Kraut, Zonderman, & Davatzikos, 2003; Salat,
Buckner, Snyder, Greve, Desikan, & Busa, 2004; Sullivan, Adalsteinsson, & Pfefferbaum, 2006;
Wen, & Sachdev, 2004). The thickness of the cortex, decreases with age, and spinal fluid levels
increase in the cranial cavity to replace lost brain volume as the brain decreases in size.
However, compensatory mechanisms are in place to overcome cognitive decline.
Recent studies reveal that short term or working memory, the ability to maintain (store)
and manipulate (process) information for short periods of time, can be improved through
cognitive training. Working memory also supports more complex cognitive functions that
include logical reasoning and problem solving, and is closely related to fluid intelligence which
relies on deductive and inductive reasoning to solve novel problems rather than crystalized
intelligence which relies on previous experiences and knowledge to problem-solve (Zinke,
Zeinti, Rose, Putzmann, & Kliegel, 2014)
These recent studies assume the principles of the disuse hypothesis in that, “… cognitive
decline in old age may be associated with a reliance on automatic modes of cognitive processing
as opposed to frequent engagement in cognitively demanding activities” (Hultsch, Hertzog,
Small, & Dixon, 1999, p.245). Kliegel, Zimprich, and Rott (2004), and Zinke, Zeintl, Rose,
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Putzmann, Pydde, and Kliegel (2014), also agreed that engagement in challenging activities
improves cognition in the aging brain and takes place whenever new learning is undertaken, with
educational settings being prime locations for older adults to improve cognition.
The Scaffolding Theory
The scaffolding theory of cognitive aging, which is based on studies using Transcranial
Magnetic Stimulation, demonstrates another compensatory mechanism that the aging brain may
use when performing cognitive tasks (Rossi, Miniussi, Pasqualetti, Babiloni, Rossini, & Cappa,
2004). Older adults show activation of both right and left hemispheres of the frontal cortex (grey
matter) in response to cognitive tasks, whereas younger adults use left lateralized activity (left
hemisphere only) for verbal recognition, working memory, semantic processing, and memory
recognition, and right lateralized activity (right hemisphere only) for face processing, spatial
working memory, and episodic recall. According to the Scaffolding Theory and supported by
Magnetic Resonance Imaging, older adults are able to recruit bilateral activation of both right
and left hemispheres of the brain for cognitive processing which younger adults are unable to do.
The aging brain responds to age related degeneration of cortical thickness and brain volume by
the enhanced recruitment of frontal structures, or scaffolding, which distributes neurons across
neural synaptic sites bilaterally, thus enabling older adults to use both hemispheres of the brain
for cognitive tasks, rather than just using the right hemisphere for certain cognitive activities and
the left hemisphere for other tasks of cognition. (Goh, & Park, 2009).
Goh and Park (2009), also indicated that the key factor in moderating the compensatory
activity is engagement in activities that enhance the ability to engage in scaffolding, including
engagement in novel activities such as participating in cognitive training strategies, or learning
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new information, which has an impact on structural development throughout the brain. An
enriched environment also promotes neuro-plasticity in older adults through novelty, and
physical exercise increases brain volume by increasing vascularization (blood flow) to the brain.
Goh and Park (2009), also refer to other studies that reveal promising results for the influence of
lifestyle factors such as an enriched environment, physical activity, and social involvement in
promoting neuro-plasticity in older adults.
Other compensatory mechanisms for age related cognitive decline have also been posited.
A number of researchers (Small, Huges, Hultsch, & Dixon, 2007; Stern, 2002, 2009), have
hypothesized a concept of passive and active cognitive reserves. The passive reserve is generally
neuron (brain cells) and synapse number (the number of connections between brain cells), brain
size and volume, cortical thickness (thickness of grey matter), and other objective indices
primarily determined by genetics. The active reserve focuses on neural processing (brain speed)
and synaptic organization (neural pathways) which includes the ability to reorganize neural
pathways through plasticity, but both are also enhanced by environmental factors such as
cognitive engagement, physical exercise, and social interactions.
Compensation is another type of active reserve in which alternate brain structures and
networks can become active following brain pathology. (Dixon, Garrett, & Blackman, 2008;
Lovden, Backman, Lindenberger, Schaefer, & Schmiedek, 2010). In other words, the active
reserve would compensate for brain injury, stroke, or old age decline, by constructing new neural
pathways through brain reconstruction (neuro-plasticity). Activities and new learning that
promote neuro-plasticity need not be formal or complicated. A unique study by Boyke,
Driemeyer, Gaser, Buchel, and May (2008), revealed that an activity as simple as learning to
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juggle balls is associated with increased cortical thickness (grey matter) in older adults due to the
visual requirement of monitoring the coordination of physical movement with active cognitive
focus. Juggling is probably an extremely difficult task for older adults to master as the physical
coordination and concentration necessary for juggling is challenging even for younger adults, but
the benefits of learning this simple and fun activity on the executive functioning process of an
aging adult brain would be invaluable.
Research studies expose participants to conditions that allow the researchers to measure
differences before and after the condition was experienced. In the case of research involving
cognitive functioning, the improvement measured after strategic cognitive training takes place is
duplicated when older adults engage in formal or informal educational endeavors, or any
experience in which new learning takes place, leading to the concept of lifelong learning as being
an essential component of healthy old age.
Lifestyles and Cognitive Decline
In the 1980s a 12-year longitudinal study of the protective effects of cognitive, physical,
and social activities on cognitive performance during the aging process revealed factors such as
improved cerebro-vascular health, decreased neuro inflammation, and enhanced cognitive
reserve, all elements that mediate the degree of brain pathology associated with normal aging
(Small, McArdle, Dixon, & Grimm, 2012). The research, consisting of predominantly Caucasian
women, (n-288), and men (n-196) between the ages of 55 and 85, was conducted every two
years, and focused on the extent that a lifestyle of physical activities, social activities and
cognitive activities acted as a buffer to age related decline in cognitive performance. A second
sample of participants was begun in the 1990s with a sample of 355 women and 175 men
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between 55 and 94 years of age. As a base line the participants were first tested using
standardized tests to assess for verbal speed processing in a word matching scenario. Next,
episodic (long term) memory was tested using word and story recall tasks; then semantic
memory of details and facts was assessed using a test of recall of world knowledge for
recognition. Lastly, a self-report standardized test was used to assess the frequency of everyday
activities that included cognitive activities such as computer use or playing cards, physical
activities such as jogging or gardening, and social activities, such as visiting friends or attending
social events. Social activities in this context were measured by the number of social resources,
and measures of social support (Bassuk, Glass, & Berkman, 1999; Seeman, Lusignolo, Albert, &
Berkman, 2001), as well as participation in social activities (Small et al., 2012). The results of
this extensive study lead the researchers to conclude that lifestyle activities in general, serve as a
protective buffer from cognitive decline. Specifically, verbal speed influenced cognitive
performance, episodic memory decreased with a decrease in both physical and cognitive
activities, and semantic memory increased with increases in social activities (Small et al., 2012).
The results of this study, especially the association between lifestyle, and active engagement in
cognitive, physical, and social pursuits that lead to an improvement of cognitive performance,
are consistent with current research in the field of aging and neuro-cognition.
Another longitudinal study of 1,135 adults 70 to 92 years of age examined the association
between educational level and cognition, using a battery of psychological and intelligence tests
to compare crystalized intelligence (previous knowledge) tasks with fluid intelligence
(reasoning) tasks. Younger adults perform rote memorization tasks, considered part of fluid
intelligence, at higher levels than older adults whereas, older adults rely on better verbal abilities
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and judgement which are considered components of crystalized intelligence (Merriam, 2001).
Several well-known and reliable tests were administered: the SLMT (Symbol Letter Modalities
Test) a timed letter substitution task, The EMT (Episodic Memory Test) of short term recall, and
the CRT test (Choice Reaction Time). These aforementioned tests, the SLMT, EMT, and CRT
are all tests of fluid intelligence. The NART (National Adult Reading Test) a test of vocabulary,
similarities, and information, and the MMSE, (Mini Mental State Examination) to test for
evidence of dementia were administered to evaluate crystalized intelligence (Christensen,
Korten, Jorm, Henderson, Jacombs, & Rodgers, 1997).
After 3.6 years a follow-up examination was performed with the remaining participants
(483 had died or were unavailable to be interviewed). This situation is inherent in any
longitudinal study conducted with older adults and leaves researchers with internal validity
issues to overcome when participants are unavailable to complete the research. Of the remaining
652 participants those with a low educational attainment were associated with a lack of
improvement in the crystalized intelligence tests including the Mini Mental State Examination,
but not on the fluid intelligence tests, thus confirming epidemiological studies by other
researchers (Colsher, & Wallace, 1991; Evans, Becket, Albert, Herbert, & Scherr, 1993; White,
Katzman, Losonczy, Salive, Wallace, Berkman, Taylor, Fillenbaum & Havlik, 1994).
Christensen et al., (1997) concluded that, “…the findings of the present study are consistent with
the operation of a compensatory process, whereby tests reflecting expertise and knowledge show
a slower rate of change. Information, Vocabulary, and Similarities [tests] were associated with
faster decline in the less well educated” (p. 328). Christensen et al., (1997) further elaborated,
“…the effect of education may compensate for rather than protect against the effects of
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biological aging” (p. 329). This study reaffirms the compensatory process taking place in the
aging brain, but asserts that the process only stabilizes the crystalized intelligence in well
educated people while having no effect on the fluid intelligence of either the educated or less
educated participants. The conclusions drawn by Christensen et al., (1997), of a compensatory
rather than protective effect of education in reducing the cognitive decline in an aging brain
reaffirms the scaffolding theory of neurogenesis: the production of new brain cells in response to
a demanding cognitive activity, such as new learning.
Four phases of cognitive decline in the second half of life were devised by Cohen (2005).
The first phase occurs between 40 and 65 years of age during a transition when children move
away and parents become, “empty nesters.” Older adults begin an evaluation of life experiences
and often “…a better coordination between the brain’s many modules, more effective integration
of the brain’s hemispheres, and more efficient signal transmission throughout the brain, all of
which support the more flexible and nuanced thinking characterized by post formal thought and
wisdom…” (p. 102). Cohen’s (2005), second phase occurs in the late 50s to early 70s. “New
neuron formation in the information processing of the brain is associated with a desire for
novelty…” and a “…desire to try something new” (p. 52). During the third phase, from the late
60s into the 90s, older adults try to find meaning in life and are motivated to share acquired
wisdom and stories with younger generations. Cohen (2005), further stated that, “bilateral
involvement of the hippocampi [used for memory storage] contribute to our capacity for
autobiographical expression” (p. 53). Among other processes, the hippocampus is responsible for
moving short term memory into long term memory. The final phase occurs in the late 70s until
life’s end. This period has identifiable changes in the brain’s amygdalae which is responsible
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for, among other processes, emotions and the monitoring of emotions. The amygdalae promotes
positive feelings, and the investigation of new ways of viewing and interpreting those feelings.
These transitional periods in the aging brain are conducive to creative activities, the exploration
of new experiences, self-reflection, experimentation, and sharing wisdom (Capps, 2012; Cohen,
2005). Cohen (2005), further elaborated:
Education for older adults should incorporate a developing paradigm
that strongly points to a more flexible balanced and efficient brain,
that is identified as, …simultaneously able to integrate left and right
hemispheres, and a maturing synergy of cognition, emotional
intelligence, judgment, life experiences, and a consciousness expressed
in deepening wisdom judgment, perspective, and vision. (pp. xix-xx)
If Cohen’s (2005) conception of the educational needs of older adults, and the complex
mechanisms of the aging brain are true, then the need for older adults to be involved in a
stimulating learning environment would be imperative, and seniors should therefore be
accommodated with learning opportunities regardless of the barriers imposed by economic,
cultural, physical, or any other limitations.
Another study using cognitive strategies such as rehearsal, feedback, and a gradual
increase in the difficulty of tasks, examined the potential for training induced neuroplasticity of
working memory in 80 adults from 65 to 95 years old. After accomplishment of the trained tasks
the participants were next tested on an untrained task to determine if a transfer of improved
cognitive ability could be maintained on new tasks. Working memory training produced gains in
training and transfer effects in the sample of participants, thus providing further evidence of
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neuro-plasticity through cognitive training interventions and the capacity to improve cognition
and brain health (Zinke, et al., 2014).
Kemperman, Gast, and Gage, (2002) found increased neuro genesis (new brain cells) in
older animals exposed to an enriched environment, suggesting that there is a potential to modify
brain structure in old age by participating in stimulating activities. Certain aspects of the
lifestyle-cognition link have been proven, others are in progress, and others have yet to be
determined but, research has proven that the link between a lifestyle that includes, physical
activity, social interaction, mentally challenging pursuits, and a healthy aging brain does exist.
The extent and implications for older adults, especially in educational environments, cannot be
understated.
Models of Aging
Erikson’s Generativity
Although Erikson described Generativity as the seventh of his eight life stages of
development in the 1950s, many researchers today have assigned the activities of Erikson’s
Generativity Model to describe older adults in the retirement years rather than at a preretirement
stage of life as Erikson envisioned (Erikson, 1982). Erikson describes the Generativity Stage as
one of caring and altruistic activities such as taking care of dependent individuals, educating and
mentoring younger generations, providing services for the needy, or being involved in social,
civil, or political activities, and contributing to society as a whole. The new generation of older
adults today are in better health, more educated, and eager to contribute to the community
(Villar, & Celdran, 2012), therefore; Erikson’s Generativity Model now applies to retirees, rather
than to an earlier pre-retirement stage of development as was the case in the 1950s. Erikson’s last
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developmental stage of life during the retirement years, Integrity, is described as a period of
quiet reflection after a life-time of developmental challenges, and was intended as a retrospective
of one’s life, but the Generativity Model best describes how the current cohort of older adults
prefer to spend retirement, a stage that Erikson believed should have already been undertaken in
the years preceding retirement (Erikson, Erikson, & Kivnick, 1986). Coincidentally, Erikson who
lived into his 90s, added another ninth developmental stage to his renowned theory on the eight
developmental stages of life, when he, himself reached what is considered old-old age--75 years
old and above (Ginsberg, & Lynn, 2002). The last stage is titled simply, Hope, and was penned
by Erikson’s spouse who survived him and continued his work. During the final stage of life
hope and faith is intended to be “…for further grace and enlightenment” (Erikson, 1997, p. 113),
but seems anticlimactic for an active life of accomplishments and endeavors.
Hierarchical Model
In response to the diversity of interests in today’s older learners, Villar and Celdran
(2012), have developed a hierarchical model of programs for senior learners. First, classes for
personal satisfaction and enjoyment. These classes are informal and promote social and leisure
activities. The second level consists classes that are educational and increase competencies,
knowledge, and personal development. At the third level programs would enable elders to
contribute to the social context in which they live by offering job skills, and training or credit
towards a degree or certificate. The salient point of Villar and Celdran’s (2012) hierarchical
model is to offer a wide range of programs to fill the range of interests, needs, and abilities of the
current cohort of older students, and allow older learners to enjoy the benefits of generativity that
Erikson described.
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Delahaye and Ehrich (2008) developed learning techniques specific to older adults using
methods based on the philosophy of humanism which focuses on the individual learner’s
personal growth and development. Under the humanist philosophy in adult education the learner
is highly motivated, self-directed, and assumes the responsibility for learning. The teacher is a
facilitator, helper, or partner who promotes, but does not direct learning, unless required to do so.
Experiential learning, freedom, self-directedness, empowerment, and interactive learning are all
hallmarks of the humanist philosophy of adult education (Zinn, 1983).
The four general themes of Delahaye and Ehrich’s (2008) learning strategies for older
adult learners are called presage factors: the learning environment, methods, and facilitation
techniques. First, are several presage factors that include a general feeling of anxiety and lack of
confidence that most learners feel entering a new learning situation. Another presage factor is the
emotional attachment to beliefs, knowledge, and world views that most individuals hold. A
certain reluctance to apply new knowledge is challenging, and requires a transformation in
learning. Mezirow (2000) described transformative learning as the ability to objectively critique
old assumptions through critical self-reflection and rational discourse to discover a new point of
view. The last presage factor is that of autonomy. Since older individuals are accustomed to
setting priorities, allocating time, and exercising judgment, opportunities to plan and control
learning activities should be integrated into the class (Spigner-Littles, & Anderson, 1999).
The next element of Delahaye and Ehrich’s (2008) learning strategies for older learners is
the learning environment. Although contrary to other researchers in the adult education field,
(Chappell, Hawke, Rhodes, & Soloman, 2003; Gelade, Catts, & Gerber, 2003; Taylor. & Rose,
2005), Delahaye and Ehrich (2008) contend that older learners feel more comfortable learning
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with cohorts of the same age. However, this statement is in direct opposition to the research
consensus, discussed earlier: that intergenerational learning provides benefits to both the younger
and the older learners (Villar, & Celdran, 2012).
Another environmental component is one of a supportive climate and a safe non-
threatening, less formal class room (Chappelle et al., 2003; Frye, 1992; Fisher, 1998). The last
aspect of an environment conducive to learning for older adults is that of peer support, peer to
peer learning, mentoring, and tutoring (Taylor, & Rose, 2005). Older learners also prefer active
group and team exercises rather than passive learning methods. Group discussions, and discovery
based content give older adults the chance for collegial learning strategies that provide a chance
to share diverse life experiences and use more mature interpersonal skills (Delahaye, & Ehrich,
2008).
The methods proposed by Delahaye and Ehrich (2008) for adult educational settings
include the teacher’s role as that of a facilitator, rather than that of teacher. The facilitator assists
learners in the construction of their own meaning of each concept presented, and enables the
learner to relate each concept to real life (Spigner-Littles, & Anderson, 1999). Taylor and Rose
(2005), propose that incorporating the need for structure with the learners need for autonomy can
be accomplished by starting with a structured class format and slowly progressing to less
structure as learners move along a continuum from low-context knowledge dependent on the
instructor to develop autonomy and reach a higher level of contextual knowledge, thus becoming
autonomous learners in incremental steps.
The last of Delahaye and Ehrich’s (2008) learning strategies for older learners is
facilitation techniques. Fisher (1998), and Spigner-Littles, and Anderson (1999), professed that
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new information needs to be connected to, and built upon prior knowledge and experiences. This
principle has been well researched by adult educators and was first proposed by Houle in 1953
(Houle, 1953). Prompt meaningful feedback using both informational and motivational elements
and the use of thoughtful probing open-ended questions that promote learners to share
knowledge with other learners (Fisher, 1998; Spigner-Littles, & Anderson, 1999).
The Gregorc Learning Style Delineator
Anthony Gregorc, an educator, developed The Gregorc Learning Style Delineator
(Gregorc, 1984) in 1982 as a psychotherapeutic instrument for school counselors and advisors.
The instrument is a self-analysis tool used to identify the method individuals habitually use to
analyze new information. This preferred method of processing input is commonly referred to as a
learning style and determines how people routinely make sense of new learning. Using
information acquired from psychoanalytically based interviews, Gregorc (1984) determined
participant’s perceptions of learning experiences using phenomenological methods and
reoccurring themes emerged. These correlations became evident from an analysis of the data and
four clusters of two sets of diametrically opposed learning styles appeared: concrete and abstract
learning orientations, and random and sequential ordering orientations. Concrete and abstract
characteristics represent opposing styles of perceptual consciousness and sequential and random
qualities represent an order of perceptions or lack of order in perceptions, respectively. The
Gregorc Learning Style Delineator was built from the data obtained from these studies and is the
instrument used in this study (Gregorc, 1984).
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Summary
In order to build a solid foundation for the results of this research a review of the
literature in areas such as the characteristics of each demographic of participants, learning
obstacles and successful strategies, biological changes in cognition, and examples of other
learning style models were presented as an overview of contemporary research. Influential
theorists and leaders in the fields of andragogy, gerontology, neurology, and other aspects of the
aging process were referenced, as input from these seemingly disparate fields was deemed
necessary to unify the research questions and understand the learning needs of older adults as a
distinct segment of our population. Next, Chapter 3 will introduce and explain the methods used
to conduct this inquiry.
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Chapter 3: Methods
Chapter 3 describes the research design and procedures used to conduct this study of the
Learning Styles of Older Adults in Educational Settings. The implementation of the Gregorc
Learning Style Delineator is more fully described and the purpose of the study, research
questions, methods, the instrument, the sample, data collection, data analysis, and a summary are
also included. The researcher (on July 25, 2013) and supervising faculty also completed
Collaborative Institutional Training Initiative (CITI) program (see Appendix A), and permission
was requested from and granted on March 26, 2015, by the Auburn University Institutional
Review Board (IRB) to conduct this study on human participants (see Appendix B). The
instrument was administered and collected directly by the researcher and transposed into
statistical data for analysis also by the researcher; therefore, participant anonymity was protected
throughout the entire study. All Auburn University protocols and procedures were followed as
well the recommendations for administration of this research survey provided in Dr. Gregorc’s
book, Development, Technical and Administration Manual (1984).
Purpose of the Study
The purpose of this study was to identify the learning styles of older adults using the
Gregorc Learning Style Delineator. In this study, older adults were ages 65 to 75 years or over
75 years of age. This study also identified race (African American or Caucasian), and sex (male
or female) as additional variables. Data were collected from participants in university life-long
learning programs, an area agency on aging, and faith-based settings. This study sought to
67
ascertain the learning styles that were used by older learners or groups of older learners.
Learning style instruments, such as the Gregorc Learning Style Delineator, assist individuals in
building an awareness or identifying learning and teaching practices that are best suited to their
own cognitive abilities.
Research Questions
The following research questions were used in this study:
1. What are the learning styles of older adults in relation to age?
2. What are the learning styles of older adults in relation to sex?
3. What are the learning styles of older adults in relation to race?
Methods
In conjunction with the instrument used--the Gregorc Learning Style Delineator--the
researcher also distributed a demographic questionnaire (see Appendix C) with each copy of the
instrument to each participant. This demographic questionnaire requested that each participant
check a box for male or female, race, White/Caucasian, Black/African American, or other, and a
blank space for the participants to record their age. After the participants completed the Gregorc
Learning Style Delineator and determined their numeric score for each of the four learning
styles: CS (Concrete Sequential), AS (Abstract Sequential), AR (Abstract Random), and CR
(Concrete Random), the participants then transposed their scores to the appropriate boxes listed
on the demographic questionnaire, which included the participant’s sex, age, race, and scores for
CS, AS, AR, and CR. Upon completion of the Gregorc Learning Style Delineator and the
demographic questionnaire, the researcher collected all of the participant’s questionnaires and
allowed participants to keep their copy of the Gregorc Learning Style Delineator as a resource
68
for future personal use. Thus anonymity was maintained throughout. Since the researcher
personally administered and collected the demographic questionnaires the response rate was
100%.
Sample
Participants
The participants for this study (n=101) were purposely selected on the basis of age. The
sample selection was parsimonious in that homogenous sampling took place with all participants
over 65 years of age, and possessed the cognitive ability to understand the questionnaire.
Geographic proximity to central Alabama also affected the sample size. The goal of the
sampling selection was to replicate the study’s results to the larger population to make inferences
and draw conclusions specific to these demographic parameters within the general population.
Age was divided into two segments of the older adult population: 65 to 74 years of age, and 75
and above. These two age segments are considered the “young old”, and the “older old”
(Ginsberg, & Lynn, 2002), and were therefore differentiated according to generational
differences. Sixty-five years of age was chosen as a starting point for this study because at 65
years of age citizens in the United States can begin to receive Social Security benefits and
medical care under the Medicare program and therefore the majority of Americans are
financially prepared to retire at 65 years old. Though not mandatory, many seniors choose to
retire at 65 years of age because of these benefits. Sex was defined as either male or female
depending on the self-identification of the participant. No identifiers were made for participants
who may be gay, bisexual, lesbian or transgender. Race was defined as either African American
69
or Caucasian with an identifier for “other” racially mixed or other racial participants. However,
there were no participants who identified their race as “other.”
Data Collection
Participants were volunteers from the Osher Lifelong Learning Institute in Auburn Alabama
(see Appendix D), The Unitarian Universalist Church in Montgomery, Alabama (see Appendix
E), and the Lee-Russell Council of Governments, Area Agency on Aging (see Appendix F),
during the months of April, May and June of 2015. The demographic questionnaire did not
include a question identifying the location of each participant; therefore, it was not possible to
determine a response rate for each location; however, since the researcher personally
administered the instrument and collected all of the demographic questionnaires the response rate
was 100%.
Statistical Methods
This research used a non-experimental design analysis because the researcher did not
manipulate any variables. Instead correlations were used to draw conclusions regarding the
incidence, distributions, and frequencies between scores on the survey. The questionnaire was
designed to capture demographic information and collect information that would enable the
researcher to conduct three chi squares: One for each demographic of the participants: age, sex,
and race using the four constructs identified by the Gregorc Learning Style Delineator: Concrete
Sequential (CS), Abstract Sequential (AS), Abstract Random (AR), and Concrete Random (CR).
Upon completion of the survey the data was collected and the information was compiled and
exported to the Statistical Package for the Social Sciences software for the appropriate analyses
70
to be run for distributions and frequencies. Figure 3.1 represents the chi square calculations for
the procedure.
𝑥𝑥2 = ∑𝑟𝑟 ∑𝑐𝑐 �𝑂𝑂𝑖𝑖𝑖𝑖− 𝐸𝐸𝑖𝑖𝑖𝑖�2
𝐸𝐸𝑖𝑖𝑖𝑖
Notation:
r = row o = observed scores
c = column e = expected scores
i = individual j = group
Figure 3.1 Chi Square Calculations
Source: Ross & Shannon, 2011
Instrumentation
An ipsative survey instrument, The Gregorc Learning Style Delineator, was used in this
research study. Dr. Anthony Gregorc who, among many other accomplishments, is a
phenomenologist who developed this instrument in 1983. Using a word association technique to
determine, “… how, why, and what individuals can, will, and do learn.” (Gregorc, 1984 p. 1),
participants rank order, a set of four words on a continuum from four to one indicating which
words best describe how the participant feels and which words most closely resemble their
manner of thinking and the method in which the individual processes new information. The
choices in each set of four words were designed to elicit an association from the individual as to
personal preferences and the thinking pattern used to learn, store, and retrieve new information.
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Dr. Gregorc developed four learning styles based on certain learning characteristics of each
individual. First, concrete sequential thinkers are based in reality and process new information in
an ordered, sequential, linear manner. These learners use their physical senses of sight, sound,
touch and smell to assess information and easily recall details, facts and formulas and rules.
These learners are “hands on” with strong organizational skills and prefer to break large projects
down into small specific steps. A quiet learning environment is needed for the concrete
sequential thinker. Next, the concrete random learner, like the concrete sequential learner is
based in reality, but are able to use more divergent thinking and like to experiment and use a
trail-and-error approach to new learning. Concrete random thinkers use intuition which leads to
more creative thought patterns and alternative viewpoints. Next, abstract random thinkers are
based in a reality of feelings and emotions, and prefer an unstructured learning environment in
which they can interact with others. Abstract random learners organize thoughts through
reflection and have a natural ability to work with others--learning by association. Lastly, abstract
sequential thinkers prefer to be alone in highly structured learning environments and enjoy
theory and abstract thought to analyze information. Abstract sequential learners are logical,
rational, and intellectual (Dryden, & Vos, 1993). Figure 3.2 provides a more comprehensive
description of the characteristics of the four Gregorc Learning Styles.
Learning Style Description of Learners Concrete Sequential (CS)
Learners prefer direct hands-on experience. They like concrete examples, actual experiences and teaching techniques that present information in an orderly sequence of connected parts: for example, they prefer topic outlines to concept maps. They prefer directions from instructors and a clearly defined student/teacher relationship. They exhibit extraordinary development of one or more of the five senses. They see situations as “black and white” or “right and wrong” and want to know the best or correct way. They apply literal meaning to verbal and written communication. They are able to approach tasks consisting of discrete
72
parts without knowing the “big picture” delay gratification until the job is complete, follow step by step directions and are attentive to details. They are organized, habitual, punctual, and desire perfection. They are the “doers.” They display a low tolerance for distractions and are practical.
Abstract Sequential (AS)
Learners prefer to deal with abstractions and avoid direct concrete experiences in favor of simulated experiences. For example, they tend to prefer lectures to lab. They prefer techniques and activities featuring substance, structure, and sequence. They are especially adept at seeing models and the “big picture.” They have excellent abilities with written, verbal, and image symbols. They like to read, listen, and use their visual skills. They expect their teachers to demonstrate expertise and authority in the classroom and to provide documentation for the ideas they present. They demonstrate good analytical and evaluative abilities. They follow guidelines reasonably well but have little acceptance of nebulous directions. They display low tolerance for distractions.
Abstract Random (AR)
Learners have a capacity to sense feelings and emotions, and use their intuition to their advantage. They prefer experiences that are subjective, affective, and abstract. They like learning options as opposed to a single fixed approach to instruction. They prefer learning in an unstructured environment, such as group discussions and activities. They prefer guidance from teachers. They are highly empathetic, can easily see the “gray” areas and see the “whole” but not the parts. They apply subjective analysis to verbal and written communications and need time to reflect and assimilate new or difficult information. They are internally motivated, expect they will perform well, and look for subjective signals of approval and disapproval. They may ignore directions and not meet deadlines. They display a reasonably high tolerance for distractions.
Concrete Random Learners prefer concrete applications of ideas through examples and practice. They like to learn independently or in small groups using trial-and-error experiments, for example they tend to prefer labs to lectures. They prefer instructional options, alternative approaches, teachers who serve as both instructors and guides. They demonstrate insight in multiple situations and can make intuitive leaps that result in creative alternative solutions to problems. They have an extraordinary ability to form relationships. They simultaneously respond to both internal and external rewards. They are problem-solvers and are application oriented, they like change and new experiences. They dislike systematic procedures and often start a new project without reading the directions. They have creative ideas, but are not the “doers.” They prefer a stimulus-rich environment and can concentrate well despite a moderate amount of distraction.
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Figure 3.2 Characteristics of Learning Styles Adapted from National American Colleges &
Teachers of Agriculture Journal, December, 2000.
Learning is described by Gregorc (1984) as a process in which individuals use different
combinations of all four basic methods to learn new information, but most people find
themselves focusing on primarily just one style. However, this primary preference was often
closely followed by a secondary style as became evident during the analysis of the scores of this
research. Thirteen participants had the same score on two different dominant learning styles
creating an unexpected overlap. The thirteen participant’s scores were considered confounded
variables and eliminated from the data analysis (Wiersma, & Jurs, 2009). Gregorc (1984)
identified learning as taking place in four main domains and developed the Learning Style
Delineator by using these four basic methods: learning by experience, learning by doing,
learning by thinking, and learning by reflection. The word choices of all four of these d as
learning methods are incorporated into the Gregorc Learning Style Delineator and are designed
to elicit favorable or less favorable responses in rank order, thus defining the participants
learning style by the association of key words.
The Instrument
Upon reading, making a decision, and numbering each box, four through one, for the first
set of four words the participant then continues to the second set of four words until all 10 sets of
words are rank ordered, four through one: four for the most preferred word association, three for
the next most preferred word, two for the next preferred word, and one for the least preferred
word association. The participant then sums the scores and places the total in a box which
designates the participant’s rating, or preference for each of the four constructs: Concrete
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Sequential, Abstract Sequential, Abstract Random, and Concrete Random. Each of the learning
styles were constructed to reveal an individual’s sub-conscious or intuitive reaction to the words
presented; therefore, revealing an assessment of each person’s most preferred learning style. The
highest numeric score is the most preferred learning style followed by a second most preferred
style and lastly the two least preferred styles (Gregorc, 1984).
Validity
There are many types of evidence for validity. In general, the two types of validity
commonly assessed are internal and external validity. “Internal validity refers to the extent to
which the results of a research study can be interpreted accurately with no plausible alternative
explanations” (Wiersma, & Jurs, 2009, p. 6). Internal validity can be undermined by several
factors. In this study internal validity could have been threatened by social interactions between
the participants which could influence the results of the data. This threat was reduced by the
researcher who requested that participants not discuss the survey until after everyone had
finished and by requesting that during the testing participants ask questions of the researcher
rather than other participants. Another threat to internal validity occurs during administration of
the instrument when social interaction between the researcher and the participants takes place.
Interviewer bias can occur and affect the validity of the data. The possibility of bias can never be
completely eliminated especially when attention to the participants being surveyed can affect the
results of the data simply by the fact that the participants know that they are being studied.
External validity refers to the extent to which the research results can be generalized to
the population at large. In the case of this study, since random selection did not take place, the
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results were generalizable only to the population within the parameters of this study as defined
by age, sex, race, and geographic location.
The level of confidence in the accuracy of the data collection instrument is also an
indication of validity (Ross, & Shannon, 2011). Therefore, relevant to this study is an assessment
of the validity and reliability of the data collection instrument--the Gregorc Learning Style
Delineator. One of the most important aspects of validity is construct validity which determines
whether the instrument measures what it is intended to measure (Wiersma, & Jurs, 2009). The
constructs of the Gregoric Learning Style Delineator are the scores pertaining to the learning
style of each participant and reveal the degree to which an individual possesses the traits
associated with each learning style. The scores should provide an accurate measure of each
participant’s learning style.
Of primary significance to this study is a type of criterion related validity--predictive
validity (Ross, & Shannon 2011), which allows the researcher to understand the degree to which
each participant relates to each of the four constructs with a numeric value or score for each
construct: Concrete Sequential, Abstract Sequential, Abstract Random, and Concrete Random.
The scores have predictive value in assigning learning characteristics or styles to each participant
and thus provide a unique teaching tool for educators and the individual by creating an
awareness of learning characteristics which can then reliably be transposed to educational
environments.
To evaluate the constructs of the instrument, correlation patterns among indicators of
each construct should correlate highly. The strength of the predictive value of the Gregorc
Learning Style Delineator to assesses the accuracy of each participant’s score and evaluate the
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degree to which the instrument actually predicts the participant’s learning style was established
by the administration of a second self-rating test using attributes that correlate with the attributes
of the instrument. The two measures are then examined for correlation using the calculation for a
correlation coefficient. A positive correlation coefficient indicates predictive validity and future
performance (Ross, & Shannon, 2009). Gregorc’s second self-rating study (n =110), when
compared to the instrument scores co-related in a range of r = 0.55 for Concrete Random to r =
0.76 for Abstract Sequential, resulting in a strong predictive validity (Gregorc, 1984).
Reliability
Reliability is the extent to which the data collection instrument yields consistent results
with minimal error (Ross, & Shannon, 2011). There are several methods to test instrument
reliability. For the purposes of this study, reliability includes consistency in the methods and
evaluation of data collection, and the extent to which the research can be replicated. Consistency
in data collection, analysis, and interpretation are known as internal reliability, while external
reliability, is the ability of other researchers, using the same methods, to be able to obtain the
same results (Wiersma, & Jurs, 2009).
To establish external reliability and repeatability Gregorc conducted a test-retest to
confirm correlation coefficients of the instrument administered at one time and again at various
intervals. Correlation coefficients between the two administrations ranged from 0.85 for
Concrete Sequential to 0.88 for Abstract Random indicating a strong degree of reliability and
repeatability (Gregorc, 1984).
The internal consistency of an instrument with a high positive index of consistency is an
indication of the reliability of the instrument (Ross, & Shannon, 2011). Gregorc’s internal
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consistency test for reliability, used correlations among items measuring the same construct
within the instrument and resulted in standardized alpha coefficients ranging from 0.89 for
Abstract Sequential to 0.93 for Abstract Random which is considered moderate to strong
consistency respectively (Gregorc, 1984).
Together, validity and reliability are the basis for evaluating each measurement used
(Ross, & Shannon, 2011), and establish the credibility of the researcher (Wiersma, & Jurs, 2009).
“Unless an instrument measures a construct consistently, it cannot be said that it is measured
accurately [validity]. Therefore, the extent to which scores are consistent tells us something
about the extent to which scores…are valid” (Ross, & Shannon, 2011, p. 243). In other words,
without reliability there can be no validity.
Data Collection
Included in the package of instruments for the Gregorc Learning Style Delineator, are
specific guidelines to be followed when administering the survey. Recommended are the
administrator’s awareness and attitude towards the participant’s apprehension of taking the
survey, and the administrator’s control of the test-taking environment to ensure that any
disturbances or noise are kept to a minimum while participants quietly reflect and consider each
word. A copy of the tri fold Gregorc Learning Style Delineator survey with the researcher’s
demographic questionnaire (see Appendix C) inserted were distributed to each of the participants
with pencils provided, and everyone was instructed to open the instrument at the same time.
Directions of how to fill out the instrument and the demographic questionnaire were then read
aloud to the participants and any questions were addressed. Participants were instructed to react
quickly to the word choices and respond instinctively rather than mull over each word choice. A
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quick reaction indicates a connection with the participant’s actual thoughts or feelings and
captures the inner processes of the mind. Administrators are cautioned that occasionally a
participant may ask for the definition of a word on the instrument. This is to be expected,
according to Dr Gregorc; however, if a participant does not know the meanings of several of the
word choices, the participant’s results would be questionable (Gregorc, 1984), and could
jeopardize the validity of the results. In order to ensure validity this researcher would discard any
data from participants who requested a definition numerous times. Although, participants at
every site often asked the researcher for a word definition no one particular individual asked for
a definition several times, and no data was eliminated or questionable; therefore, maintaining
validity.
Upon completion of the instrument several participants needed assistance in scoring and
transposing the scores to the demographic questionnaire. Participants shared their scores with
other participants and discussed results with the researcher as the researcher collected the
demographic questionnaires and reminded the participants that there is no correct or incorrect
learning style and directed their attention to a chart with a more detailed style comparison listed
on the back of the instrument which the participants were allowed to take home and peruse at
their leisure.
Data Analysis
The data results from the demographic questionnaire were entered into the Statistical
Package for the Social Sciences (SPSS). Frequencies and three chi squares were performed on
each of the four constructs of the Gregorc Learning Style Delineator: Concrete Sequential,
Abstract Sequential, Abstract Random, and Concrete Random. The quantitative data collected
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measured the numeric scores on the survey and the chi squares provided correlations between the
demographic questionnaire and scores on the Gregorc Learning Style Delineator, allowing the
researcher to determine the dominant learning style for each particular variable: sex, race, and
age.
Summary
Chapter 3 has provided a detailed description of the procedures used in conducting this
research. Information on the sample of participants, the site locations of each group of
participants, the methods used to collect the data, statistical information including validity and
reliability concerns, and a description of the instrument, the Gregorc Learning Style Delineator,
which included an analysis of the reliability and validity of the instrument (Gregorc, 1984). The
statistical methods, formula, and analysis of the data were all explained in sufficient detail to
allow duplication of the research. The research design also provided viable data, yielding
important information on the dominant learning style of older adults in relation to age, sex, and
race, including how older adults prefer to learn: Invaluable information to both educators and
older adult learners. Chapter 4 will next discuss the findings of the statistical analysis described
in this chapter.
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Chapter 4: Findings
In Chapter 4 the statistical results of this study are provided to identify the learning style
preferences of each group of participants and answer the three specific research questions
regarding age, sex, and race. Chapter 4 is organized in terms of the three specific research
questions posed in Chapter 1 and conveys the results of the data analysis in either narrative or
table format with major findings highlighted and briefly summarized. Topics include:
demographic results, statistical frequencies, results by age, sex, and race, chi squares, the results,
and a summary.
Purpose of the Study
The purpose of this study was to identify the learning styles of older adults using the
Gregorc Learning Style Delineator. In this study, older adults were ages 65 to 75 years or over
75 years of age. This study also identified race (African American or Caucasian), and sex (male
or female) as additional variables. Data were collected from participants in university life-long
learning programs, an area agency on aging, and faith-based settings. This study sought to
ascertain the learning styles that were used by older learners or groups of older learners.
Learning style instruments, such as the Gregorc Learning Style Delineator, assist individuals in
building an awareness or identifying learning and teaching practices that are best suited to their
own cognitive abilities.
81
Research Questions
The following research questions were used in this study:
1. What are the learning styles of older adults in relation to age?
2. What are the learning styles of older adults in relation to sex?
3. What are the learning styles of older adults in relation to race?
Demographic Results
Population Characteristics
One-hundred and one participants were surveyed for this research study using the
Gregorc Learning Style Delineator. Participants were recruited from the Osher Lifelong Learning
Institute at Auburn University, Auburn AL, the Unitarian Universalist Fellowship of
Montgomery AL, and the Lee-Russell Council of Governments Area Agency on Aging, Opelika
AL between the months of March and April of 2015. The only requirement to volunteer for the
study was that all participants must be 65 years of age and older.
Statistical Frequencies
Of the 101 participants, 72 or 71.3% identified as female and 29 or 28.7% identified as
males. The largest demographic of participants at 79 or 78.2% identified as Caucasian, and 22 or
21.8% identified as African American. In the category of age 71 or 70.3% of the participants
were 65 to 75 years of age and far outnumbered the 30 or 29.7% participants who were over age
75. The sample population was predominantly female, predominantly Caucasian, and in the 65 to
75-year-old age category.
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Learning Style Frequencies
As presented in Table 1 of the four learning styles described by Gregorc, Concrete
Sequential was the most preferred learning style among all participants (n = 39). The scores for
Abstract Random, Concrete Random, and Abstract Sequential were evenly spread among the
remaining 49 participants. Of the 101 participants 13 had two identical scores on the survey.
Rather than having one dominant learning style, these participants had equal scores on two
dominant learning styles. Data from these participants were not included in the data analysis
leaving the total number of participants at 88 (n = 88). This reduction in n was accounted for in
the statistical results of Style Preferences reported in Table 1.
Table 1
Gregorc Learning Style Preferences
Frequency Percent Valid Percent Cumulative Percent
Concrete Sequential
39 38.6 44.3 44.3
Abstract Sequential
14 13.9 15.9 60.2
Abstract Random
18 17.8 20.5 80.7
Concrete Random
17 16.8 19.3 100
Total 88 87.1 100
Missing 13 12.9
Total 101 100.0
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What are the Learning Styles of Older Adults in Relation to Age?
The chi square analysis for the learning style differences between participants 65 to 75,
and 76 and above, revealed a two-sided significance of X² =.760 which is >.05 indicating no
statistical significance in the distribution of learning styles in regard to the two age groups.
Table 2 lists the observed counts and expected counts by age group for each learning style of the
Gregorc Learning Style Delineator. The learning style differences by age were relatively evenly
spread for each age group, with Concrete Sequential being the preferred style for each group.
Table 2
Gregorc Learning Style Delineator Results by Age
Age Count Learning Styles
CS AS AR CR
65-75 Count 28 8 13 12
Expected Count
27.0 9.7 12.5 11.8
76 and Above
Count 11 6 5 5
Expected Count
12.0 4.3 5.5 5.2
What are the Learning Styles of Older Adults in Relation to Sex ?
The chi square analysis for the learning style differences between male and female
participants revealed a two-sided significance of X² =.579 which is >.05 indicating no statistical
significance in the distribution of learning styles in regard to the sex of the participants. The
female participant’s scores were evenly spread with the exception of Concrete Sequential which
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was the preferred learning style for both sexes. The males scores were the most evenly spread
among all participants with Concrete Sequential preferred over Abstract Random by only 2
individuals. Table 3 presents the counts and expected counts by sex for each learning style of the
Gregorc Learning Style Delineator.
Table 3
Gregorc Learning Style Delineator Results by Sex
Sex Count Learning Styles
CS AS AR CR
Female Count 30 9 11 11
Expected Count
27.0 9.7 12.5 11.8
Male
Count 9 5 7 6
Expected Count
12.0 4.3 5.5 5.2
What are the Learning Styles of Older Adults in Relation to Race?
The chi square analysis for the learning style differences between Caucasian and African
American participants revealed a two sided significance of X² = .026 which is <.05 indicating
statistical significance in the distribution of learning styles between the two racial groups. In this
case, a X² =.026 is important because the implication is that there are statistically significant
differences in the learning styles of African Americans compared to Caucasians, and that the
observed results actually reflect the characteristics of the participants and are not due to a
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sampling error (Wiersma, & Jurs, 2009). The learning style preferences were more evenly
spread with Caucasian participants than with African American participants; however, Concrete
Sequential was the preferred learning style for each group. Table 4 presents the counts and
expected counts by Caucasian and African American participants for each learning style
construct of the Gregorc Learning Style Delineator.
Table 4
Gregorc Learning Style Delineator Results by Race
Race Count Learning Styles
CS AS AR CR
Caucasian Count 25 12 13 17
Expected Count
29.7 10.7 13.7 12.9
African American
Count 14 2 5 0
Expected Count
9.3 3.3 4.3 4.1
Chi Square Tests
The chi square results, as presented in Table 5 yielded values of: age X² =.760, sex = .579
and race at X² =.026. These values were compared to the alpha level of < 0.05 and with a chi
square of .026 only the African American and Caucasian groups reached statistically significant
values in this study of differences in learning styles using the Gregorc Learning Style Delineator.
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Table 5
Chi Square Values of Age, Sex, and Race
Value df Asymptomatic Significance
(2-sided) Age Pearson Chi Square 1.173 3 .760
Sex Pearson Chi Square 1.967 3 .579
Race Pearson Chi Square 9.295 3 .026
Phi Coefficients
The Phi coefficient is a measure of association between nominal variables. Table 6
presents a comparison of Phi coefficients with the chi square analyses which were all of equal
values; however; none reached statistical significance (p <.05) except the chi square for race at
.026. The Phi coefficients for age at .760 and sex at .579 indicated a relatively weak and weak
positive association respectively. Only the African American and Caucasian groups reached
statistically significant values in this study of differences in learning styles using the Gregorc
Learning Style Delineator. Therefore, the differences in learning styles between African
Americans and Caucasians must be considered in multi-racial learning environments.
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Table 6
Measures of Association of Chi Squares and Phi Coefficients
Phi Coefficients Chi Squares Phi Values
Age .760 .760 .115
Sex .579 .579 .150
Race .026 .026 .325
Results
To determine the differences in the learning style preferences of the variables age, sex,
and race, three two-sample chi square analyses were conducted on the three independent
samples. Each variable had two levels: sixty-five to seventy-five years of age, and over seventy-
five years of age, male/female, and African American/Caucasian. An alpha level of < 0.05 was
used to determine statistical significance as is standard for research in the social sciences, and
three degrees of freedom (df) were used for each chi square analysis.
Summary
In this research study the statistical analysis clearly indicated that there was no difference
in learning styles in regard to age or sex. In answer to question one, “What are the learning styles
of older adults in relation to age?” There was no statistically significant difference in the learning
styles of young-older adults aged 65 to 75 and old-older adults aged 76 and above at X² = .760.
In answer to question two, “What are the learning styles of older adults in relation to sex?” There
was no statistically significant difference in learning styles in relation to male or female at X²
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=.579. In answer to question three, “What are the learning styles of older adults in relation to
race?” There was a statistically significant difference between African Americans and Caucasian
older adults at X²=.026. The chi square analysis for race did reach statistical significance
suggesting that Caucasian and African American participants differed in learning style
preferences. A deeper analysis of the findings and a detailed summary will be discussed further
in Chapter 5 with implications of the results and recommendations for future research.
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Chapter 5: Summary, Conclusions. Implications,
and Recommendations for Future Research
Research Questions
The following research questions were used in this study:
1. What are the learning styles of older adults in relation to age?
2. What are the learning styles of older adults in relation to sex?
3. What are the learning styles of older adults in relation to race?
Summary
Learning Styles of Older Adults in Educational Settings is an examination into the
learning styles of the baby boomer generation who are now entering retirement. With typical
retirement at 65 years of age and life expectancy now 80 to 85 years of age, millions of retirees
will have fifteen to twenty years of healthy retirement to fill. This change has created a new
demographic of older adults--baby boomers. Today’s seniors want to be productive during
retirement and many plan to use those years to fulfill dreams and goals postponed during child
rearing years, or when careers took priority. The activities seniors want to pursue will require
further education, training, or new learning and millions of older adults will be entering learning
environments to acquire the skills necessary to remain active and engaged during the retirement
years (Narushima, Liu, & Diestelkamp, 2013; Parks, Evans, & Getcg, 2013).
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Studies reveal that remaining actively involved in life and pursuing new learning
experiences promotes not only a longer life but, a healthier, more fulfilling, and meaningful life
in the senior years, reducing the dependency on social services and thus taxpayers (Pew
Research Center, 2009). Universities, community colleges, technical, and trade schools, as well
as civic organizations, government agencies, and non-profit organizations must be prepared to
meet the learning needs of this new demographic of older adults who will be entering retirement
and seeking educational opportunities that will allow them to fully participate in a healthy
lifestyle, both mentally and physically. This study was conducted to determine the learning style
preferences of older adults, and will provide information for educators and instructors to adapt to
the needs of this new demographic of learners. Participants were surveyed by age, race, and sex
using the four constructs of the Gregorc Learning Style Delineator: Concrete Sequential,
Abstract Sequential, Concrete Random and Abstract Random.
Three chi square analyses were conducted to assess the learning preference of each of the
participants according to each category of age, sex, and race with results indicating categorical
preferences. Learning style preferences showed no statistical significance between different ages
and sexes. However, the difference between the learning style preferences by race was
statistically significant. Individual characteristics vary, but this research provides generalizations
as a guideline to assess learner needs and will be of vital importance to the success of new
learning for our older adult population especially in racially diverse learning environments.
Conclusions
The number of older Americans is increasing exponentially and the US must contend
with numerous challenges in meeting the learning needs of this diverse group of seniors.
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Strategic planning and implementation of learning strategies specifically for older learners is of
major concern to educators and integral to the success of the older learner in educational settings.
The Gregorc Learning Style Delineator was selected as the instrument to conduct this
study of the learning style preferences of older adults by sex, age, and race. However, the
statistical results of this study indicated no statistically significant differences between
participants of different sexes or ages. A statistically significant learning style difference
between African American and Caucasian participants was found. The differences or lack of
differences in learning styles among these groups of participants could be attributed to the
limitations of this study, or any number of other factors beyond the scope of this research.
However, a similar study by Truluck and Courtenay (1999), also found no statistical
significance in learning style preference between older adults in regard to sex or age groups.
Using Kolb’s (1985) Learning Style Inventory, and 172 participants, the researchers divided the
older adults into three age groups: 55 to 65 years old, 66 to 74 years old and over 75 years old. A
chi-square analysis of the association between sex and learning style revealed no statistical
significance; moreover, each of the three age groups did differ in their learning style preference,
though not at statistically significant levels. The 55 to 65-year-old age group preferred Kolb’s
Accommodator learning style, the 66 to 74-year-old group preferred the Diverger learning style,
and the 75 and over age group preferred the Assimilator learning style (Truluck & Courtenay,
1999). Although Truluck and Courtenay used a different learning style instrument, a similar
population, and data analysis revealed similar results: no statistical significance in regard to sex
or age. Race was not considered in Truluck and Courtenay’s research, but speculation would lead
92
to an assumption that a statistical significance between races could have been reached as was the
case in this researcher’s findings.
Implications
Educator Implications
In this study the results from the Gregorc Learning Style Delineator identified the
learning style preferences of participants in regard to sex, age, and race and will allow educators
and instructors to develop a broader understanding of learning style needs. These learning styles
needs could be incorporated into the Needs Assessment phase of the generic instructional design
model, ADDIE (Assess needs, Design lessons, Develop classes, Implement lessons, and Evaluate
classes). Participants in this study were considerably more Concrete Sequential (n =39). Abstract
Random had the next greatest frequency (n=18), Concrete Random was less frequent (n =17),
and Abstract Sequential was the least frequent (n =14).
The results of this study indicate that most older learners of either sex and Caucasians or
African Americans are Concrete Sequential learners which leads to a recommendation of
teaching directed to the Concrete Sequential learning style. However, as evidenced-based
teaching suggests a variety of teaching strategies incorporated into every learning experience will
enhance the learning process for learners (Buskist & Groccia, 2011).
Being aware of the constructs of the Gregorc Learning Style Delineator will also allow
educators and instructors to evaluate the learning characteristics of individual students and
modify classroom structure and lessons to include learning strategies to best facilitate learning
that includes different learning styles.. Figure 5.1 suggests teaching methods that match each of
the four constructs of the Gregorc Learning Style Delineator.
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Figure 5.1 Teaching Strategies to Match Gregorc Learning Styles
Source: National American Colleges and Teachers of Agriculture Journal, 2000.
Concrete Sequential
• Use models and drawings • Use direction sheets • Ordered presentations and lectures • Workbooks and lab manuals • Hands-on building projects • Programed or computer assisted instruction • Structured field trips
Abstract Sequential
• Reading assignments • Well organized and meaningful lectures • Audiotapes and CD,s • Debates
Abstract Random
• Group discussion • Short reading assignments followed by class activities • Small group discussions • Audiovisual programs • Assignments that permit reflection and thinking time
Concrete Random
• Trial and error • Games and simulations • Independent study projects • Optional reading assignments • Mini-lectures that set up a problem situation
NACTA Journal, 2000.
94
Participant Implications
The different learning styles developed by Anthony Gregorc are intended to guide
individuals in becoming more self-aware and thus enable the participant a better understanding
of themselves, how they learn new information, and problem solve. This identification of a
particular learning preference to gain new information and knowledge allows older adults to
apply the characteristics of their dominant learning style to any type of learning environment.
The participants also develop a more complete concept of themselves and their world view and
are able to apply their individual learning style to any future endeavors in educational programs,
classes, lessons, training, or any situation that requires new learning
Each participant was also allowed to retain their copy of the Gregorc Learning Style
Delineator with a 14 item in-depth description of each learning style provided on the back of
every survey for participants to review later and assess their score in-depth, thus allowing
participants to fully benefit from the evaluation experience. The tri-fold Gregorc Learning Style
Delineator also considerately provides a graph for participants to chart their scores for a visual
representation of their learning style rather than a numeric rating. The graph provides a visual
scale for the participants to determine how their dominant learning style aligns with the other
learning styles. An awareness of their preferred learning style and the information included with
the survey can build confidence and empower older adults to continue to contribute to society in
a fulfilling and meaningful manner.
Recommendations for Future Research
The identification and familiarization of different learning styles will also allow
educators to apply specific learning strategies to teaching practices. The information provided in
95
this study will not only assist learners and educators, but administrators, policy makers,
community leaders, faith-based organizations, and non-profits will benefit from an understanding
of different methods to develop class structure that accommodates the learning needs of older
employees, volunteers, and students in a wide variety of learning environments.
In accordance with the findings of this research a deeper investigation into the results of
this study would be invaluable in determining the rationale behind the similarities and
dissimilarities in the groups of participants. For example, no statistical significance was found
between the learning style preferences of older males and females, or between the young-old and
the older-old participants. The inherent cognitive differences between men and women are well-
documented and somewhat understood, yet the findings of this study revealed that learning style
preferences are not dissimilar. Why? Further research could provide evidence of similar
cognitive patterns in older men and women. The similarities between the two generations of
baby boomers—the young-old and the older-old—are also recommended for further
investigation. The “generation gap” is a well-known discrepancy between generations, yet this
study found no significant differences in learning styles. Why? The conjecture that perhaps we
are all more alike than different is a possibility, but requires more evidenced based inquiry.
Future research could also expand on this study by increasing the sample size, extending
the geographical area to urban areas, or other regions of the United States and diversifying the
racial composition. African Americans and Caucasians participated in this study, but additional
Asian, Hispanic, and other minority populations would further enhance an understanding of the
possible racial differences in learning styles. Also, as an expansion of the findings in this study a
focus on the learning preferences of older Americans would broaden the scope of the
96
investigation of learning styles and lead to more successful teaching modalities that could better
adapt to our aging population. Therefore, an investigation into the factors that underlie the results
of this study would be recommended for future research.
Another recommendation worthy of investigation is research into the learning styles of
marginalized groups of our aging society. Trans-gender, gay, and lesbian individuals, new
immigrants, nursing home residents, frail or physically challenged individuals, and the
incarcerated would all benefit from an assessment of their learning style while adding to the
scientific body of knowledge on older learners and their impact on our future.
Evidence exists that individuals of certain occupations have similar learning styles
(Wenham & Alie, 1992). Future studies of the learning styles of older adults by occupation or
previous job should reveal an association between job and learning style. Ginsberg (2002)
included marital status and education level in her study of learning styles and older adults using
Kolb’s Learning Style Inventory Version 3 and phenomenological methods. Future studies using
the more definitive Gregorc Learning Style Delineator and older participants grouped by
educational level could reveal significant differences.
As Erik Erikson so succinctly expressed in his 1986 book, Vital Involvement in Old Age,
“Can we now progress to a genuine valuing of old age with rights and responsibilities
appropriate to the summing up of a life-time” (p. 305)? Indeed, these words although expressed
30 years ago resound today. Perhaps, as baby boomers change our conception of old age, as they
have for each life stage that they have transitioned through and redefined by their sheer numbers,
a new paradigm for the last stage of life will come into existence.
97
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